dataset_version stringclasses 1
value | configuration stringclasses 1
value | split stringclasses 1
value | source stringclasses 1
value | stream_id stringclasses 23
values | stream_seed int64 26.4M 4.24B | stream_order int32 | seed_group int64 | episode_index int32 0 7 | episode_id stringlengths 27 27 | task_id stringlengths 34 34 | task_family stringclasses 1
value | experience_type stringclasses 2
values | slot_role stringclasses 2
values | support listlengths 8 8 | query listlengths 8 8 | probe_prompts listlengths 8 8 | future_reuse_prob float32 0 1 | n_future_occurrences int32 0 2 | total_occurrences int32 1 3 | version int32 1 1 | revises stringclasses 0
values | source_item_id stringlengths 24 24 | source_case_id stringclasses 0
values | stream_metadata_json stringclasses 1
value | episode_metadata_json stringlengths 251 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 0 | adaptable_train_0000::ep000 | adaptable:38c9eca4cce6d373e2327329 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Name] Red Sonja [Type]\n[Type] =",
"target": "Character",
"candidates": [
"Character",
"User"
],
"source": "UnpredicTable",
"source_id": "49bb098c_wahlur_rising_s_Following_List__Type",
"metadata... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] Set [Type]\n[Type] =",
"target": "Character",
"candidates": [
"Character",
"User"
],
"source": "UnpredicTable",
"source_id": "49bb098c_wahlur_rising_s_Following_List__Type",
"me... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] fukuro_zoku [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] Solomon Kane [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the r... | 0 | 0 | 1 | 1 | null | 38c9eca4cce6d373e2327329 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "38c9eca4cce6d373e2327329", "source_rows": 50, "source_task_id": "49bb098c_wahlur_rising_s_Following_List__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 1 | adaptable_train_0000::ep001 | adaptable:62c2f4dcfd481ff8a32ae740 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] Yosemite marks its 150 years [Author] webmaster [Type]\n[Type] =",
"target": "Article",
"candidates": [
"Article",
"Blog Post"
],
"source": "UnpredicTable",
"source_id": "5492e319_ontent___www... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Oz plays Madera [Author] webmaster [Type]\n[Type] =",
"target": "Blog Post",
"candidates": [
"Article",
"Blog Post"
],
"source": "UnpredicTable",
"source_id": "5492e319_ontent___ww... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Day without printing not worth it [Author] webmaster [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Validation for Redskins player [Author] webmaster [Type]\n[Type] =... | 0 | 0 | 1 | 1 | null | 62c2f4dcfd481ff8a32ae740 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "62c2f4dcfd481ff8a32ae740", "source_rows": 25, "source_task_id": "5492e319_ontent___www_maderatribune_com__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 2 | adaptable_train_0000::ep002 | adaptable:b899bef90f4748959011f7be | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Spell] Burning Vapors [Level] 5 [Description] Generates a burning cloud of gas that travels forth, damaging any enemies within the cloud and setting them ablaze. [Type]\n[Type] =",
"target": "Instant",
"candidates": [
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Spell] Magic Missile [Level] 2 [Description] Fires a minor magical projectile at your current target that explodes upon impact, blasting any enemies within the radius of the explosion. [Type]\n[Type] =",
"target": "... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Spell] Freezing Touch [Level] 1 [Description] Surrounds your melee weapon or fist in a frigid aura, allowing you to freeze opponents by striking them. [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Typ... | 0.5 | 1 | 2 | 1 | null | b899bef90f4748959011f7be | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "b899bef90f4748959011f7be", "source_rows": 24, "source_task_id": "704d14e3_GameBanshee__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 3 | adaptable_train_0000::ep003 | adaptable:274257139af111cec1cfc823 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Thesis Course] for the row.\n[ID] 455 [Class] MBA [Topics] Impact of monetary policy on GDP of Pakistan [Thesis Course]\n[Thesis Course] =",
"target": "Economics",
"candidates": [
"Economics",
"Finance",
"Human Resource Manage... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Thesis Course] for the row.\n[ID] 299 [Class] MBA [Topics] Impact of mood on Brand Recall & Attitude of brand placement in television program [Thesis Course]\n[Thesis Course] =",
"target": "Marketing",
"candidates": [
"Economi... | [
"Apply the learned table pattern for a table task. Predict [Thesis Course] for the row.\n[ID] 374 [Class] MBA [Topics] Effect of communication during an acquisition on employees behavioral outcomes [Thesis Course]\n[Thesis Course] =",
"Apply the learned table pattern for a table task. Predict [Thesis Course] for ... | 0 | 0 | 1 | 1 | null | 274257139af111cec1cfc823 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "274257139af111cec1cfc823", "source_rows": 723, "source_task_id": "98a4bafd_earch_Topics___Iqra_University__Thesis_Course", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 4 | adaptable_train_0000::ep004 | adaptable:b8622701610a3b9b5721bcd5 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Forum] for the row.\n[Title] Board & Batten Siding on SIPs [Author] brucebuilder [Replies] 7 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Construction Techniques",
"candidates": [
"Construction Techniques",
"Energy, Heati... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Choosing a multi tool [Author] bergsteiger1 [Replies] 10 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Tools for Home Building",
"candidates": [
"Construction Techniques",
"Energy, ... | [
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] How to eliminate a 4-way light switch? [Author] bergsteiger1 [Replies] 2 [Last Post] 2 years ago [Forum]\n[Forum] =",
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Deteriorating wood... | 1 | 2 | 3 | 1 | null | b8622701610a3b9b5721bcd5 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "b8622701610a3b9b5721bcd5", "source_rows": 25, "source_task_id": "54ed4bfe__Fine_Homebuilding___Breaktime__Forum", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 5 | adaptable_train_0000::ep005 | adaptable:b899bef90f4748959011f7be | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Spell] Burning Vapors [Level] 5 [Description] Generates a burning cloud of gas that travels forth, damaging any enemies within the cloud and setting them ablaze. [Type]\n[Type] =",
"target": "Instant",
"candidates": [
"In... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Spell] Magic Missile [Level] 2 [Description] Fires a minor magical projectile at your current target that explodes upon impact, blasting any enemies within the radius of the explosion. [Type]\n[Type] =",
"target": "... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Spell] Freezing Touch [Level] 1 [Description] Surrounds your melee weapon or fist in a frigid aura, allowing you to freeze opponents by striking them. [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Typ... | 0.5 | 0 | 2 | 1 | null | b899bef90f4748959011f7be | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "b899bef90f4748959011f7be", "source_rows": 24, "source_task_id": "704d14e3_GameBanshee__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 6 | adaptable_train_0000::ep006 | adaptable:b8622701610a3b9b5721bcd5 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Forum] for the row.\n[Title] Board & Batten Siding on SIPs [Author] brucebuilder [Replies] 7 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Construction Techniques",
"candidates": [
"Construction Techniques",
"Energy, Heating &... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Choosing a multi tool [Author] bergsteiger1 [Replies] 10 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Tools for Home Building",
"candidates": [
"Construction Techniques",
"Energy, ... | [
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] How to eliminate a 4-way light switch? [Author] bergsteiger1 [Replies] 2 [Last Post] 2 years ago [Forum]\n[Forum] =",
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Deteriorating wood... | 1 | 1 | 3 | 1 | null | b8622701610a3b9b5721bcd5 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "b8622701610a3b9b5721bcd5", "source_rows": 25, "source_task_id": "54ed4bfe__Fine_Homebuilding___Breaktime__Forum", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0000 | 2,157,557,608 | null | null | 7 | adaptable_train_0000::ep007 | adaptable:b8622701610a3b9b5721bcd5 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Forum] for the row.\n[Title] Board & Batten Siding on SIPs [Author] brucebuilder [Replies] 7 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Construction Techniques",
"candidates": [
"Construction Techniques",
"Energy, Heating &... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Choosing a multi tool [Author] bergsteiger1 [Replies] 10 [Last Post] 3 years ago [Forum]\n[Forum] =",
"target": "Tools for Home Building",
"candidates": [
"Construction Techniques",
"Energy, ... | [
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] How to eliminate a 4-way light switch? [Author] bergsteiger1 [Replies] 2 [Last Post] 2 years ago [Forum]\n[Forum] =",
"Apply the learned table pattern for a table task. Predict [Forum] for the row.\n[Title] Deteriorating wood... | 1 | 0 | 3 | 1 | null | b8622701610a3b9b5721bcd5 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "b8622701610a3b9b5721bcd5", "source_rows": 25, "source_task_id": "54ed4bfe__Fine_Homebuilding___Breaktime__Forum", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 0 | adaptable_train_0001::ep000 | adaptable:b723bf6aa1243386b0e393c4 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerLook [Product] ProductViper NT [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids All Designer Select Water-Based Fog Fluids [Application]\n[Application] =",
"target": "Applicatio... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerElektralite [Product] Productmini turbofog [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids All Water-Based Fog Fluids by Froggy's Fog [Application]\n[Application] =",
... | [
"Apply the learned table pattern for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerSuperior [Product] ProductST-10 Super Fogger [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids Fire Rescue (Longer Lasting), Fire Rescue SM (Higher Density) [Application]\n[Application] ... | 0.5 | 1 | 2 | 1 | null | b723bf6aa1243386b0e393c4 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "b723bf6aa1243386b0e393c4", "source_rows": 317, "source_task_id": "03327e6c_uice_and_Bubbles___Froggys_Fog__Application", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 1 | adaptable_train_0001::ep001 | adaptable:54860daee2046b2d3e2c318c | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Track] for the row.\n[Session] Chorion: Migrating and Consolidating Localised Branded Web Sites With Drupal Chorion is the owner of a number of major brands which it develops globally through the production of family entertainment. Historically Chorion... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Track] for the row.\n[Session] E-Commerce - The Benefits of Using Drupal , , More information is coming soon [Track]\n[Track] =",
"target": "Day Stage",
"candidates": [
"Business Day",
"Business and Best Practices",
... | [
"Apply the learned table pattern for a table task. Predict [Track] for the row.\n[Session] How Do You Know that Gal Knows Drupal? Towards an Open Source Curriculum and a Community-Based Accreditation Scheme for Drupal , As Drupal grows, so do the challenges of identifying and developing Drupal talent. Gone are the ... | 0 | 0 | 1 | 1 | null | 54860daee2046b2d3e2c318c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "54860daee2046b2d3e2c318c", "source_rows": 48, "source_task_id": "057ab02b_ssions___DrupalCon_London_2011__Track", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 2 | adaptable_train_0001::ep002 | adaptable:a08727bdf14c6c677f6f9069 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Result] for the row.\n[Pitch] 25 [Type] Breaking Ball [Location] Inside Low [4] Swinging Strike [Stance] LH [Result]\n[Result] =",
"target": "Swings",
"candidates": [
"Swings",
"Takes"
],
"source": "UnpredicTable",
"sour... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Result] for the row.\n[Pitch] 3 [Type] Fastball [Location] Outside Middle [4] Foul Ball [Stance] RH [Result]\n[Result] =",
"target": "Swings",
"candidates": [
"Swings",
"Takes"
],
"source": "UnpredicTable",
"... | [
"Apply the learned table pattern for a table task. Predict [Result] for the row.\n[Pitch] 37 [Type] Fastball [Location] Outside Middle [4] Pop Foul to C [Stance] LH [Result]\n[Result] =",
"Apply the learned table pattern for a table task. Predict [Result] for the row.\n[Pitch] 30 [Type] Fastball [Location] Inside... | 0 | 0 | 1 | 1 | null | a08727bdf14c6c677f6f9069 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "a08727bdf14c6c677f6f9069", "source_rows": 40, "source_task_id": "1a058ead_Grandal___redsminorleagues_com__Result", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 3 | adaptable_train_0001::ep003 | adaptable:164709c309f3ae6802418e5e | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Protected Score] for the row.\n[seg1] OK [seg2] OK [seg3] F [action] mandatory reride only if distance is best distance in skiers turn [Protected Score]\n[Protected Score] =",
"target": "No",
"candidates": [
"No",
"Yes",
"Yes ... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Protected Score] for the row.\n[seg1] S [seg2] S [seg3] S [action] optional reride (protected score) [Protected Score]\n[Protected Score] =",
"target": "Yes",
"candidates": [
"No",
"Yes",
"Yes if OR No if MR",
... | [
"Apply the learned table pattern for a table task. Predict [Protected Score] for the row.\n[seg1] F [seg2] F [seg3] OK [action] mandatory reride only if distance is best distance in skiers turn [Protected Score]\n[Protected Score] =",
"Apply the learned table pattern for a table task. Predict [Protected Score] fo... | 0 | 0 | 1 | 1 | null | 164709c309f3ae6802418e5e | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "164709c309f3ae6802418e5e", "source_rows": 27, "source_task_id": "ff861174__Federation_Tournament_Council__Protected_Score", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 4 | adaptable_train_0001::ep004 | adaptable:0382a69a7da41140ffc0820c | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] this is a example, if someone need it sometime [Author] gjg [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum topic",
"Question",
"Script"
],
"sou... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Can I get gimp to open a new file, add effects, then export to a jpg with script-fu? [Author] saulgoode [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum ... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Hi- I've been trying to use the hexgrid plugin and it invariably crashes- it shuts GIMP down in the process. What am I doing Wrong (I'm using vr.2.8 with Win7). [Author] Jack Cass [Views today] 0 [Type]\n[Type] =",
"Apply the ... | 1 | 2 | 3 | 1 | null | 0382a69a7da41140ffc0820c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0382a69a7da41140ffc0820c", "source_rows": 24, "source_task_id": "56025b09_content___GIMP_Plugin_Registry__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 5 | adaptable_train_0001::ep005 | adaptable:b723bf6aa1243386b0e393c4 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerLook [Product] ProductViper NT [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids All Designer Select Water-Based Fog Fluids [Application]\n[Application] =",
"target": "Application Fo... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerElektralite [Product] Productmini turbofog [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids All Water-Based Fog Fluids by Froggy's Fog [Application]\n[Application] =",
... | [
"Apply the learned table pattern for a table task. Predict [Application] for the row.\n[Manufacturer] ManufacturerSuperior [Product] ProductST-10 Super Fogger [Fluid Type] Fluid TypeWater-based Froggys Fog Recommended Fluids Fire Rescue (Longer Lasting), Fire Rescue SM (Higher Density) [Application]\n[Application] ... | 0.5 | 0 | 2 | 1 | null | b723bf6aa1243386b0e393c4 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "b723bf6aa1243386b0e393c4", "source_rows": 317, "source_task_id": "03327e6c_uice_and_Bubbles___Froggys_Fog__Application", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 6 | adaptable_train_0001::ep006 | adaptable:0382a69a7da41140ffc0820c | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Title] this is a example, if someone need it sometime [Author] gjg [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum topic",
"Question",
"Script"
],
"source"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Can I get gimp to open a new file, add effects, then export to a jpg with script-fu? [Author] saulgoode [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum ... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Hi- I've been trying to use the hexgrid plugin and it invariably crashes- it shuts GIMP down in the process. What am I doing Wrong (I'm using vr.2.8 with Win7). [Author] Jack Cass [Views today] 0 [Type]\n[Type] =",
"Apply the ... | 1 | 1 | 3 | 1 | null | 0382a69a7da41140ffc0820c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0382a69a7da41140ffc0820c", "source_rows": 24, "source_task_id": "56025b09_content___GIMP_Plugin_Registry__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0001 | 26,368,601 | null | null | 7 | adaptable_train_0001::ep007 | adaptable:0382a69a7da41140ffc0820c | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Title] this is a example, if someone need it sometime [Author] gjg [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum topic",
"Question",
"Script"
],
"source"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Can I get gimp to open a new file, add effects, then export to a jpg with script-fu? [Author] saulgoode [Views today] 0 [Type]\n[Type] =",
"target": "Answer",
"candidates": [
"Answer",
"Forum ... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Hi- I've been trying to use the hexgrid plugin and it invariably crashes- it shuts GIMP down in the process. What am I doing Wrong (I'm using vr.2.8 with Win7). [Author] Jack Cass [Views today] 0 [Type]\n[Type] =",
"Apply the ... | 1 | 0 | 3 | 1 | null | 0382a69a7da41140ffc0820c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0382a69a7da41140ffc0820c", "source_rows": 24, "source_task_id": "56025b09_content___GIMP_Plugin_Registry__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 0 | adaptable_train_0002::ep000 | adaptable:df93eeea5983bf2b13b5f6b6 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Rating] for the row.\n[State Laws] Illinois when the violation results in great bodily harm or disfigurement to another and is a class 4 felony [Rating]\n[Rating] =",
"target": "specific",
"candidates": [
"specific",
"vague"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Virginia driving too fast for conditions [Rating]\n[Rating] =",
"target": "vague",
"candidates": [
"specific",
"vague"
],
"source": "UnpredicTable",
"source_id": "2a4dc5c7_C... | [
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Washington stopping on the roadway [Rating]\n[Rating] =",
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Maryland drives a motor vehicle in a deliberately discourteous, in... | 1 | 2 | 3 | 1 | null | df93eeea5983bf2b13b5f6b6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "df93eeea5983bf2b13b5f6b6", "source_rows": 29, "source_task_id": "2a4dc5c7_Charts___Handouts__Rating", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 1 | adaptable_train_0002::ep001 | adaptable:df93eeea5983bf2b13b5f6b6 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Rating] for the row.\n[State Laws] Illinois when the violation results in great bodily harm or disfigurement to another and is a class 4 felony [Rating]\n[Rating] =",
"target": "specific",
"candidates": [
"specific",
"vague"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Virginia driving too fast for conditions [Rating]\n[Rating] =",
"target": "vague",
"candidates": [
"specific",
"vague"
],
"source": "UnpredicTable",
"source_id": "2a4dc5c7_C... | [
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Washington stopping on the roadway [Rating]\n[Rating] =",
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Maryland drives a motor vehicle in a deliberately discourteous, in... | 1 | 1 | 3 | 1 | null | df93eeea5983bf2b13b5f6b6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "df93eeea5983bf2b13b5f6b6", "source_rows": 29, "source_task_id": "2a4dc5c7_Charts___Handouts__Rating", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 2 | adaptable_train_0002::ep002 | adaptable:2c06fb896fbc0377318eef95 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] Believing Is Seeing [Type]\n[Type] =",
"target": "Editorial",
"candidates": [
"Editorial",
"Feature Article",
"Interview",
"Locational",
"Media Review",
"News Article",
"Pers... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Business, Faith, and Climate Change: A Conversation with Mindy Lubber and Reverend Sally Bingham [Type]\n[Type] =",
"target": "Interview",
"candidates": [
"Editorial",
"Feature Article",
... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] China’s Down to the Last Drop [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Women Managing Farms and Forests in South Asia [Type]\n[Type] =",
"Apply the learned ta... | 0 | 0 | 1 | 1 | null | 2c06fb896fbc0377318eef95 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "2c06fb896fbc0377318eef95", "source_rows": 25, "source_task_id": "9a301991_Popular_content___Solutions__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 3 | adaptable_train_0002::ep003 | adaptable:cde367f0afcf339cc0df6ea8 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Course Type] for the row.\n[Course Name] Science - Common Entry [Course Code] CI061LA LY857 CCNMX [Course Type]\n[Course Type] =",
"target": "Higher Education Direct Entry",
"candidates": [
"Higher Education Direct Entry",
"Lifelong... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Tourism & Airline Studies / Business [Course Code] 5M5011 CI061TA [Course Type]\n[Course Type] =",
"target": "PLC Post Leaving Cert",
"candidates": [
"Higher Education Direct Entry",
... | [
"Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Architectural Technology & Design Year 2 [Course Code] 6M4989 CI062AT [Course Type]\n[Course Type] =",
"Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Certified... | 0.5 | 1 | 2 | 1 | null | cde367f0afcf339cc0df6ea8 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "cde367f0afcf339cc0df6ea8", "source_rows": 151, "source_task_id": "3744a328__s_National_Learners__Database__Course_Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 4 | adaptable_train_0002::ep004 | adaptable:ec1e76af41f06918eb6bb5ea | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Consensus] for the row.\n[#] 36 [Type] Site [Factor] Manual Authority/Weight Given to Site by Google [Importance] Medium [Consensus]\n[Consensus] =",
"target": "No",
"candidates": [
"No",
"Somewhat",
"Yes"
],
"source":... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Consensus] for the row.\n[#] 42 [Type] In-Link [Factor] Temporal Link Attributes (when in time the link was created/updated) [Importance] Medium [Consensus]\n[Consensus] =",
"target": "Somewhat",
"candidates": [
"No",
"S... | [
"Apply the learned table pattern for a table task. Predict [Consensus] for the row.\n[#] 12 [Type] Page [Factor] Quality/Relevance of Links to External Sites/Pages [Importance] High [Consensus]\n[Consensus] =",
"Apply the learned table pattern for a table task. Predict [Consensus] for the row.\n[#] 10 [Type] In-L... | 0 | 0 | 1 | 1 | null | ec1e76af41f06918eb6bb5ea | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "ec1e76af41f06918eb6bb5ea", "source_rows": 53, "source_task_id": "ef1cdf87_Factors_2007___Quick_Reference__Consensus", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 5 | adaptable_train_0002::ep005 | adaptable:cde367f0afcf339cc0df6ea8 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Course Type] for the row.\n[Course Name] Science - Common Entry [Course Code] CI061LA LY857 CCNMX [Course Type]\n[Course Type] =",
"target": "Higher Education Direct Entry",
"candidates": [
"Higher Education Direct Entry",
"Lifelong Lea... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Tourism & Airline Studies / Business [Course Code] 5M5011 CI061TA [Course Type]\n[Course Type] =",
"target": "PLC Post Leaving Cert",
"candidates": [
"Higher Education Direct Entry",
... | [
"Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Architectural Technology & Design Year 2 [Course Code] 6M4989 CI062AT [Course Type]\n[Course Type] =",
"Apply the learned table pattern for a table task. Predict [Course Type] for the row.\n[Course Name] Certified... | 0.5 | 0 | 2 | 1 | null | cde367f0afcf339cc0df6ea8 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "cde367f0afcf339cc0df6ea8", "source_rows": 151, "source_task_id": "3744a328__s_National_Learners__Database__Course_Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 6 | adaptable_train_0002::ep006 | adaptable:1b6b9b63b954e0f0a71d4c3d | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [GENDER] for the row.\n[NAME] Tsukuba Goyo [SERIES] Shadow Arts [GENDER]\n[GENDER] =",
"target": "Female",
"candidates": [
"Female",
"Male"
],
"source": "UnpredicTable",
"source_id": "71d33458_cters___Fighting_Game_Databa... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [GENDER] for the row.\n[NAME] Takuma Sakazaki [SERIES] Art of Fighting [GENDER]\n[GENDER] =",
"target": "Male",
"candidates": [
"Female",
"Male"
],
"source": "UnpredicTable",
"source_id": "71d33458_cters___Fig... | [
"Apply the learned table pattern for a table task. Predict [GENDER] for the row.\n[NAME] Tyrone [SERIES] Street Combat [GENDER]\n[GENDER] =",
"Apply the learned table pattern for a table task. Predict [GENDER] for the row.\n[NAME] Trigger Happy [SERIES] Double Dragon V [GENDER]\n[GENDER] =",
"Apply the learned ... | 0 | 0 | 1 | 1 | null | 1b6b9b63b954e0f0a71d4c3d | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster13.parquet", "source_item_id": "1b6b9b63b954e0f0a71d4c3d", "source_rows": 70, "source_task_id": "71d33458_cters___Fighting_Game_Database__GENDER", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0002 | 2,068,370,739 | null | null | 7 | adaptable_train_0002::ep007 | adaptable:df93eeea5983bf2b13b5f6b6 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Rating] for the row.\n[State Laws] Illinois when the violation results in great bodily harm or disfigurement to another and is a class 4 felony [Rating]\n[Rating] =",
"target": "specific",
"candidates": [
"specific",
"vague"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Virginia driving too fast for conditions [Rating]\n[Rating] =",
"target": "vague",
"candidates": [
"specific",
"vague"
],
"source": "UnpredicTable",
"source_id": "2a4dc5c7_C... | [
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Washington stopping on the roadway [Rating]\n[Rating] =",
"Apply the learned table pattern for a table task. Predict [Rating] for the row.\n[State Laws] Maryland drives a motor vehicle in a deliberately discourteous, in... | 1 | 0 | 3 | 1 | null | df93eeea5983bf2b13b5f6b6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "df93eeea5983bf2b13b5f6b6", "source_rows": 29, "source_task_id": "2a4dc5c7_Charts___Handouts__Rating", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 0 | adaptable_train_0003::ep000 | adaptable:e97ec42843d11375bd9eccdc | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Field] post_live_fitness_activity_twitter [Description] true if live activities are automatically posted to Twitter, false otherwise [Editable] Y [Type]\n[Type] =",
"target": "Boolean",
"candidates": [
"Boolean",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Field] post_diabetes_facebook [Description] true if diabetes measurements are automatically posted to Facebook, false otherwise [Editable] Y [Type]\n[Type] =",
"target": "Boolean",
"candidates": [
"Boolean... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Field] post_background_activity_facebook [Description] true if background activities are automatically posted to Facebook, false otherwise [Editable] Y [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Ty... | 0 | 0 | 1 | 1 | null | e97ec42843d11375bd9eccdc | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "e97ec42843d11375bd9eccdc", "source_rows": 30, "source_task_id": "0e84a668_HealthGraph_nd_com_runkeeper_Settings_json_Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 1 | adaptable_train_0003::ep001 | adaptable:f67a4bd7caca2ea9959f94f7 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Gender] for the row.\n[#] 31 [Style] Semi Contact [Level] beginner [Age] Older Cadet 13>/15 Years Old [Division] -52kg [Gender]\n[Gender] =",
"target": "Boys",
"candidates": [
"Boys",
"Girls",
"Men",
"Mixed",
"Open... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 97 [Style] Semi Contact [Level] Brown/Black (Advanced) [Age] 19 Years & Over [Division] -70kg [Gender]\n[Gender] =",
"target": "Women",
"candidates": [
"Boys",
"Girls",
"Men",
"Mixed... | [
"Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 23 [Style] Semi Contact [Level] Intermediate/Advanced [Age] Younger Cadet <12 - Years Old [Division] -28kg [Gender]\n[Gender] =",
"Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 82 [Style] S... | 0.5 | 1 | 2 | 1 | null | f67a4bd7caca2ea9959f94f7 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "f67a4bd7caca2ea9959f94f7", "source_rows": 179, "source_task_id": "7f1ccac2_Sports_Competitions__Made_Easy__Gender", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 2 | adaptable_train_0003::ep002 | adaptable:5be05a984a13cb0c9de77642 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [0] for the row.\n[Application Number] RB5-07349 [Board approved?] No [Title] Investigating nucleotide deficiency-based genomic instability in hIPSCs [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07380 [Board approved?] No [Title] Human nephron progenitors and renal specification [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
"Recom... | [
"Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07210 [Board approved?] Yes [Title] New Regulators of Spermatogonial Stem Cells: RHOX Homeobox Transcription Factors [Score] 76 [0]\n[0] =",
"Apply the learned table pattern for a table task. Predict [0] for the ... | 1 | 2 | 3 | 1 | null | 5be05a984a13cb0c9de77642 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "5be05a984a13cb0c9de77642", "source_rows": 62, "source_task_id": "88355959__California_s_Stem_Cell_Agency__0", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 3 | adaptable_train_0003::ep003 | adaptable:f67a4bd7caca2ea9959f94f7 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Gender] for the row.\n[#] 31 [Style] Semi Contact [Level] beginner [Age] Older Cadet 13>/15 Years Old [Division] -52kg [Gender]\n[Gender] =",
"target": "Boys",
"candidates": [
"Boys",
"Girls",
"Men",
"Mixed",
"Open",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 97 [Style] Semi Contact [Level] Brown/Black (Advanced) [Age] 19 Years & Over [Division] -70kg [Gender]\n[Gender] =",
"target": "Women",
"candidates": [
"Boys",
"Girls",
"Men",
"Mixed... | [
"Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 23 [Style] Semi Contact [Level] Intermediate/Advanced [Age] Younger Cadet <12 - Years Old [Division] -28kg [Gender]\n[Gender] =",
"Apply the learned table pattern for a table task. Predict [Gender] for the row.\n[#] 82 [Style] S... | 0.5 | 0 | 2 | 1 | null | f67a4bd7caca2ea9959f94f7 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "f67a4bd7caca2ea9959f94f7", "source_rows": 179, "source_task_id": "7f1ccac2_Sports_Competitions__Made_Easy__Gender", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 4 | adaptable_train_0003::ep004 | adaptable:5be05a984a13cb0c9de77642 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [0] for the row.\n[Application Number] RB5-07349 [Board approved?] No [Title] Investigating nucleotide deficiency-based genomic instability in hIPSCs [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07380 [Board approved?] No [Title] Human nephron progenitors and renal specification [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
"Recom... | [
"Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07210 [Board approved?] Yes [Title] New Regulators of Spermatogonial Stem Cells: RHOX Homeobox Transcription Factors [Score] 76 [0]\n[0] =",
"Apply the learned table pattern for a table task. Predict [0] for the ... | 1 | 1 | 3 | 1 | null | 5be05a984a13cb0c9de77642 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "5be05a984a13cb0c9de77642", "source_rows": 62, "source_task_id": "88355959__California_s_Stem_Cell_Agency__0", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 5 | adaptable_train_0003::ep005 | adaptable:5be05a984a13cb0c9de77642 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [0] for the row.\n[Application Number] RB5-07349 [Board approved?] No [Title] Investigating nucleotide deficiency-based genomic instability in hIPSCs [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07380 [Board approved?] No [Title] Human nephron progenitors and renal specification [Score] 0 [0]\n[0] =",
"target": "Not recommended",
"candidates": [
"Not recommended",
"Recom... | [
"Apply the learned table pattern for a table task. Predict [0] for the row.\n[Application Number] RB5-07210 [Board approved?] Yes [Title] New Regulators of Spermatogonial Stem Cells: RHOX Homeobox Transcription Factors [Score] 76 [0]\n[0] =",
"Apply the learned table pattern for a table task. Predict [0] for the ... | 1 | 0 | 3 | 1 | null | 5be05a984a13cb0c9de77642 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "5be05a984a13cb0c9de77642", "source_rows": 62, "source_task_id": "88355959__California_s_Stem_Cell_Agency__0", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 6 | adaptable_train_0003::ep006 | adaptable:3d3f26dbb11d224856687b9c | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [1] for the row.\n[0] Supplementary Product Disclosure Statement (SPDS) [2] Business Insurance Business Insurance for Professionals Trade Insurance [1]\n[1] =",
"target": "An SPDS updates or adds to the information in the PDS.",
"candidates": [
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] W [2] Applies to [1]\n[1] =",
"target": "Meaning",
"candidates": [
"An SPDS updates or adds to the information in the PDS.",
"An incident you did not intend or expect to happen.",
"Meaning",
... | [
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] C [2] Applies to [1]\n[1] =",
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] D [2] Applies to [1]\n[1] =",
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] R [2] App... | 0 | 0 | 1 | 1 | null | 3d3f26dbb11d224856687b9c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "3d3f26dbb11d224856687b9c", "source_rows": 25, "source_task_id": "158d160b_y__Terms_and_Definitions___GIO__1", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0003 | 3,821,755,203 | null | null | 7 | adaptable_train_0003::ep007 | adaptable:6afec3af10ddb989ad901bdc | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Frequency] for the row.\n[Item] Paint Can (Purple) [Last VU] 9.4.1 [Frequency]\n[Frequency] =",
"target": "Common",
"candidates": [
"Common",
"Event",
"Extremely rare",
"Often",
"Rare",
"Uncommon",
"Unk... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Frequency] for the row.\n[Item] Basic Strategic Combat Processor [Last VU] 9.4.4 [Frequency]\n[Frequency] =",
"target": "Uncommon",
"candidates": [
"Common",
"Event",
"Extremely rare",
"Often",
"Rare",
... | [
"Apply the learned table pattern for a table task. Predict [Frequency] for the row.\n[Item] Tripudion skin [Last VU] 10.4.2 [Frequency]\n[Frequency] =",
"Apply the learned table pattern for a table task. Predict [Frequency] for the row.\n[Item] Advanced Scanning Sensor [Last VU] 9.3.2 [Frequency]\n[Frequency] =",... | 0 | 0 | 1 | 1 | null | 6afec3af10ddb989ad901bdc | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "6afec3af10ddb989ad901bdc", "source_rows": 32, "source_task_id": "00a01e54_opia_Universe_Guides_Wiki_Info__Frequency", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 0 | adaptable_train_0004::ep000 | adaptable:e3d66ad3f9c26d80c45d3a24 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [School] for the row.\n[Undergraduate Major] Music [Track] Music and Worship [Degree Type] Bachelor of Arts [School]\n[School] =",
"target": "Arts and Humanities",
"candidates": [
"Arts and Humanities",
"Business",
"Education a... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Computer Science [Degree Type] Bachelor of Arts [School]\n[School] =",
"target": "Natural and Social Sciences",
"candidates": [
"Arts and Humanities",
"Business",
"Educat... | [
"Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Biblical Studies [Degree Type] Bachelor of Arts [School]\n[School] =",
"Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Drama [Degree Type] Bachelor of Art... | 0.5 | 1 | 2 | 1 | null | e3d66ad3f9c26d80c45d3a24 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "e3d66ad3f9c26d80c45d3a24", "source_rows": 102, "source_task_id": "422762c5_University_Majors__School", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 1 | adaptable_train_0004::ep001 | adaptable:0e4f70955542035809d153a2 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 1KY [Description of Service] Flat Two Way (coin or coinless) [Availability] IA, ID N, ID S, MN, NE, ND, OR, SD, UT, WA, WY [Type of PAL Service]\n[Type of PAL Service] =",
"target": "Basic"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 19V [Description of Service] Measured Two-Way service restricts outgoing Operator assisted toll calls to collect, bill to Third Party and Calling Card Calls [Availability] AZ* [Type... | [
"Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 12R [Description of Service] Measured Outgoing Only includes Outgoing Call Screening, Pay per Call Blocking [Availability] IA [Type of PAL Service]\n[Type of PAL Service] =",
"Apply the learned t... | 1 | 2 | 3 | 1 | null | 0e4f70955542035809d153a2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0e4f70955542035809d153a2", "source_rows": 42, "source_task_id": "e2e35db7_tail_Public_Access_Lines__PAL___Type_of_PAL_Service", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 2 | adaptable_train_0004::ep002 | adaptable:e3d66ad3f9c26d80c45d3a24 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [School] for the row.\n[Undergraduate Major] Music [Track] Music and Worship [Degree Type] Bachelor of Arts [School]\n[School] =",
"target": "Arts and Humanities",
"candidates": [
"Arts and Humanities",
"Business",
"Education and P... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Computer Science [Degree Type] Bachelor of Arts [School]\n[School] =",
"target": "Natural and Social Sciences",
"candidates": [
"Arts and Humanities",
"Business",
"Educat... | [
"Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Biblical Studies [Degree Type] Bachelor of Arts [School]\n[School] =",
"Apply the learned table pattern for a table task. Predict [School] for the row.\n[Undergraduate Major] Drama [Degree Type] Bachelor of Art... | 0.5 | 0 | 2 | 1 | null | e3d66ad3f9c26d80c45d3a24 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "e3d66ad3f9c26d80c45d3a24", "source_rows": 102, "source_task_id": "422762c5_University_Majors__School", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 3 | adaptable_train_0004::ep003 | adaptable:0e4f70955542035809d153a2 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 1KY [Description of Service] Flat Two Way (coin or coinless) [Availability] IA, ID N, ID S, MN, NE, ND, OR, SD, UT, WA, WY [Type of PAL Service]\n[Type of PAL Service] =",
"target": "Basic",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 19V [Description of Service] Measured Two-Way service restricts outgoing Operator assisted toll calls to collect, bill to Third Party and Calling Card Calls [Availability] AZ* [Type... | [
"Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 12R [Description of Service] Measured Outgoing Only includes Outgoing Call Screening, Pay per Call Blocking [Availability] IA [Type of PAL Service]\n[Type of PAL Service] =",
"Apply the learned t... | 1 | 1 | 3 | 1 | null | 0e4f70955542035809d153a2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0e4f70955542035809d153a2", "source_rows": 42, "source_task_id": "e2e35db7_tail_Public_Access_Lines__PAL___Type_of_PAL_Service", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 4 | adaptable_train_0004::ep004 | adaptable:41c6351b20179ef5ca85ab1a | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Mod] for the row.\n[Command/CVAR] cg_debuganim [Mode] Client [Description] At 1, spams console with the animations as they are sctivated [c] [Mod]\n[Mod] =",
"target": "ETMain",
"candidates": [
"ETMain",
"ETPro"
],
"source":... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Mod] for the row.\n[Command/CVAR] cg_teamChatTime [Mode] Client [Description] Duration (team?) chatsare displayed for [Mod]\n[Mod] =",
"target": "ETMain",
"candidates": [
"ETMain",
"ETPro"
],
"source": "UnpredicT... | [
"Apply the learned table pattern for a table task. Predict [Mod] for the row.\n[Command/CVAR] b_weapaltReloads [Mode] Client [Description] Toggles weapalt reloading [Mod]\n[Mod] =",
"Apply the learned table pattern for a table task. Predict [Mod] for the row.\n[Command/CVAR] s_musicvolume [Mode] Client [Descripti... | 0 | 0 | 1 | 1 | null | 41c6351b20179ef5ca85ab1a | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "41c6351b20179ef5ca85ab1a", "source_rows": 965, "source_task_id": "c96e479d_rritory_Commands_and_Cvar_List__Mod", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 5 | adaptable_train_0004::ep005 | adaptable:20be470b9d05a8f0d0296b2b | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] JCE 90.02—February 2013 Issue Highlights [Author] Mary Saecker [Type]\n[Type] =",
"target": "Article",
"candidates": [
"Article",
"Blog entry",
"Landing page",
"Pick",
"Video"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Electrical conductivity of hydrochloric acid [Author] Anonymous (not verified) [Type]\n[Type] =",
"target": "Video",
"candidates": [
"Article",
"Blog entry",
"Landing page",
"Pick"... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] The Book Nobody Read: Chasing the Revolutions of Nicolaus Copernicus [Author] Hal Harris [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] JCE Special Issue Call For Pap... | 0 | 0 | 1 | 1 | null | 20be470b9d05a8f0d0296b2b | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "20be470b9d05a8f0d0296b2b", "source_rows": 25, "source_task_id": "07fac509_t___Chemical_Education_Xchange__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 6 | adaptable_train_0004::ep006 | adaptable:1b9ffc72bbe3900d15f95fe5 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] 2011 Anime Minicon Art Contest Winners [Type]\n[Type] =",
"target": "Article",
"candidates": [
"Article",
"Blog entry",
"Image",
"Page",
"Webform"
],
"source": "UnpredicTable",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Books, Movies & Music [Type]\n[Type] =",
"target": "Page",
"candidates": [
"Article",
"Blog entry",
"Image",
"Page",
"Webform"
],
"source": "UnpredicTable",
"sour... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Young People's Creative Writing Contest [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] 2015 Young People's Creative Writing Contest [Type]\n[Type] =",
"Apply the le... | 0 | 0 | 1 | 1 | null | 1b9ffc72bbe3900d15f95fe5 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "1b9ffc72bbe3900d15f95fe5", "source_rows": 25, "source_task_id": "89dac165_Popular_content___TCCL_Teens__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0004 | 3,337,407,669 | null | null | 7 | adaptable_train_0004::ep007 | adaptable:0e4f70955542035809d153a2 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 1KY [Description of Service] Flat Two Way (coin or coinless) [Availability] IA, ID N, ID S, MN, NE, ND, OR, SD, UT, WA, WY [Type of PAL Service]\n[Type of PAL Service] =",
"target": "Basic",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 19V [Description of Service] Measured Two-Way service restricts outgoing Operator assisted toll calls to collect, bill to Third Party and Calling Card Calls [Availability] AZ* [Type... | [
"Apply the learned table pattern for a table task. Predict [Type of PAL Service] for the row.\n[Class of Service USOC] 12R [Description of Service] Measured Outgoing Only includes Outgoing Call Screening, Pay per Call Blocking [Availability] IA [Type of PAL Service]\n[Type of PAL Service] =",
"Apply the learned t... | 1 | 0 | 3 | 1 | null | 0e4f70955542035809d153a2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "0e4f70955542035809d153a2", "source_rows": 42, "source_task_id": "e2e35db7_tail_Public_Access_Lines__PAL___Type_of_PAL_Service", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 0 | adaptable_train_0005::ep000 | adaptable:c7660df43138b36c289988d9 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Ploidy] for the row.\n[Name] My Friend Floyd [Price] SOLD OUT [Hybridizer] Roberts [Size] Large Bloom [Habit] Semi Evergreen [6] SOLD OUT [Ploidy]\n[Ploidy] =",
"target": "Diploid",
"candidates": [
"Diploid",
"Tetraploid"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Ploidy] for the row.\n[Name] Gavin Petit [Price] SOLD OUT [Hybridizer] Petit [Size] Large Bloom [Habit] Semi-Evergreen [6] SOLD OUT [Ploidy]\n[Ploidy] =",
"target": "Tetraploid",
"candidates": [
"Diploid",
"Tetraploid"
... | [
"Apply the learned table pattern for a table task. Predict [Ploidy] for the row.\n[Name] Dewey Roquemore [Price] $4.95 [Hybridizer] Warner [Size] Large Bloom [Habit] Dormant [6] Add To Cart [Ploidy]\n[Ploidy] =",
"Apply the learned table pattern for a table task. Predict [Ploidy] for the row.\n[Name] Webster Lupt... | 0 | 0 | 1 | 1 | null | c7660df43138b36c289988d9 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "c7660df43138b36c289988d9", "source_rows": 1752, "source_task_id": "e3294935_Smokeys_Daylily_Gardens__Ploidy", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 1 | adaptable_train_0005::ep001 | adaptable:90110827d653fba67218a48f | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Specialty Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
"source_id":... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Emergency First Response Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
... | [
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] IDC Staff Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Care for ... | 1 | 2 | 3 | 1 | null | 90110827d653fba67218a48f | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "90110827d653fba67218a48f", "source_rows": 36, "source_task_id": "0a446d9b_Dive_Oahu__808_922_3483__eLearning_Available_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 2 | adaptable_train_0005::ep002 | adaptable:4bcf1be1627fb70015e5d946 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Category] for the row.\n[Title] Choosing Your Battles [Author] Nancy Sander [Category]\n[Category] =",
"target": "Parenting Solutions",
"candidates": [
"Parenting Solutions",
"Teen Health",
"Teen Issues",
"Teen Parenting... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Teen Boarding Schools - Teen Help is Here [Author] Jake Richey [Category]\n[Category] =",
"target": "Teen Parenting Advice",
"candidates": [
"Parenting Solutions",
"Teen Health",
"Te... | [
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Teen Boot Camp Questions [Author] Nancy Sander [Category]\n[Category] =",
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Parents: What You Need To Know About Your Teen And Drugs... | 0.5 | 1 | 2 | 1 | null | 4bcf1be1627fb70015e5d946 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "4bcf1be1627fb70015e5d946", "source_rows": 34, "source_task_id": "82194b73_Teen_Parenting_Articles__Category", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 3 | adaptable_train_0005::ep003 | adaptable:c0e39a326938aa860a684ad5 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Frequency] for the row.\n[Tumour type] Pituitary adenoma [Classification] Pituitary tumor [Predilection site] Diencephalon [Pathology] Solitary [Frequency]\n[Frequency] =",
"target": "Common",
"candidates": [
"Common",
"Rare",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Frequency] for the row.\n[Tumour type] Medulloblastoma [Classification] Primitive neuroectodermal tumor [Predilection site] Diencephalon [Pathology] Solitary [Frequency]\n[Frequency] =",
"target": "Rare",
"candidates": [
"Comm... | [
"Apply the learned table pattern for a table task. Predict [Frequency] for the row.\n[Tumour type] Ganglioneuroblastoma [Classification] Nerve cell tumor [Predilection site] Cerebrum [Pathology] Solitary [Frequency]\n[Frequency] =",
"Apply the learned table pattern for a table task. Predict [Frequency] for the ro... | 0 | 0 | 1 | 1 | null | c0e39a326938aa860a684ad5 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "c0e39a326938aa860a684ad5", "source_rows": 26, "source_task_id": "d71e5d72_Brain_tumors___Dog__Frequency", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 4 | adaptable_train_0005::ep004 | adaptable:90110827d653fba67218a48f | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Specialty Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
"source_id": "0a... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Emergency First Response Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
... | [
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] IDC Staff Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Care for ... | 1 | 1 | 3 | 1 | null | 90110827d653fba67218a48f | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "90110827d653fba67218a48f", "source_rows": 36, "source_task_id": "0a446d9b_Dive_Oahu__808_922_3483__eLearning_Available_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 5 | adaptable_train_0005::ep005 | adaptable:4bcf1be1627fb70015e5d946 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Category] for the row.\n[Title] Choosing Your Battles [Author] Nancy Sander [Category]\n[Category] =",
"target": "Parenting Solutions",
"candidates": [
"Parenting Solutions",
"Teen Health",
"Teen Issues",
"Teen Parenting Adv... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Teen Boarding Schools - Teen Help is Here [Author] Jake Richey [Category]\n[Category] =",
"target": "Teen Parenting Advice",
"candidates": [
"Parenting Solutions",
"Teen Health",
"Te... | [
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Teen Boot Camp Questions [Author] Nancy Sander [Category]\n[Category] =",
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Title] Parents: What You Need To Know About Your Teen And Drugs... | 0.5 | 0 | 2 | 1 | null | 4bcf1be1627fb70015e5d946 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "4bcf1be1627fb70015e5d946", "source_rows": 34, "source_task_id": "82194b73_Teen_Parenting_Articles__Category", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 6 | adaptable_train_0005::ep006 | adaptable:1688acff730fc82457d12e92 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Status] for the row.\n[Topic] Version 1.4 update question started by wintner [Posts] 5 [Last post] wintner [Status]\n[Status] =",
"target": "Not Resolved",
"candidates": [
"Not Resolved",
"Not Support",
"Resolved"
],
"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Status] for the row.\n[Topic] Past Events NOT SHOWING! PLEASE Help started by tmizzone [Posts] 11 [Last post] wintner [Status]\n[Status] =",
"target": "Not Resolved",
"candidates": [
"Not Resolved",
"Not Support",
... | [
"Apply the learned table pattern for a table task. Predict [Status] for the row.\n[Topic] Past Events NOT SHOWING! PLEASE Help started by s3 [Posts] 5 [Last post] Chrismarks [Status]\n[Status] =",
"Apply the learned table pattern for a table task. Predict [Status] for the row.\n[Topic] New version still does not ... | 0 | 0 | 1 | 1 | null | 1688acff730fc82457d12e92 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "1688acff730fc82457d12e92", "source_rows": 50, "source_task_id": "1546496f_esh_Creative_WordPress_Themes___Status", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0005 | 2,304,822,676 | null | null | 7 | adaptable_train_0005::ep007 | adaptable:90110827d653fba67218a48f | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Specialty Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
"source_id": "0a... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Emergency First Response Learn More [eLearning Available?]\n[eLearning Available?] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
... | [
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] IDC Staff Instructor Learn More [eLearning Available?]\n[eLearning Available?] =",
"Apply the learned table pattern for a table task. Predict [eLearning Available?] for the row.\n[Course Title] Care for ... | 1 | 0 | 3 | 1 | null | 90110827d653fba67218a48f | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "90110827d653fba67218a48f", "source_rows": 36, "source_task_id": "0a446d9b_Dive_Oahu__808_922_3483__eLearning_Available_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 0 | adaptable_train_0006::ep000 | adaptable:b55d97bdd73158d55c5c4ce2 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Charles from USA Termites and traditional harvest and fashioning.\n[Do you talk with your friends and audience about how a didj is made?] =",
"ta... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Rik Van Luijn from Netherlands I let them look in to the bottom of an originally termite hollowed didj and one that was drilled out by a ... | [
"Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Scott from Australia Find the stick you want and put it on a termites nest until ready then decorate\n[Do you talk with your friends and audience about h... | 1 | 2 | 3 | 1 | null | b55d97bdd73158d55c5c4ce2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster26.parquet", "source_item_id": "b55d97bdd73158d55c5c4ce2", "source_rows": 103, "source_task_id": "ba0586f5_finest_online_didgeridoo_store__ence_about_how_a_didj_is_made_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 1 | adaptable_train_0006::ep001 | adaptable:b55d97bdd73158d55c5c4ce2 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Charles from USA Termites and traditional harvest and fashioning.\n[Do you talk with your friends and audience about how a didj is made?] =",
"target... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Rik Van Luijn from Netherlands I let them look in to the bottom of an originally termite hollowed didj and one that was drilled out by a ... | [
"Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Scott from Australia Find the stick you want and put it on a termites nest until ready then decorate\n[Do you talk with your friends and audience about h... | 1 | 1 | 3 | 1 | null | b55d97bdd73158d55c5c4ce2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "recurrence", "source_file": "unpredictable_cluster26.parquet", "source_item_id": "b55d97bdd73158d55c5c4ce2", "source_rows": 103, "source_task_id": "ba0586f5_finest_online_didgeridoo_store__ence_about_how_a_didj_is_made_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 2 | adaptable_train_0006::ep002 | adaptable:c5dc2ed8243eadfd70446749 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Category] for the row.\n[Treatment] Osteofos D3 (calcium plus vitamin d) [Patients] 0 [Category]\n[Category] =",
"target": "Nutrition/Diet",
"candidates": [
"Nutrition/Diet",
"Other",
"Over the Counter Drug",
"Physical T... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Treatment] Ostiva (multivitamins and minerals) [Patients] 0 [Category]\n[Category] =",
"target": "Supplement",
"candidates": [
"Nutrition/Diet",
"Other",
"Over the Counter Drug",
"Phy... | [
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Treatment] Osteotomy of foot [Patients] 0 [Category]\n[Category] =",
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Treatment] Osteotomy of mandible [Patients] 0 [Category]\n[Category] =",
... | 0 | 0 | 1 | 1 | null | c5dc2ed8243eadfd70446749 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "c5dc2ed8243eadfd70446749", "source_rows": 30, "source_task_id": "4ad15f49_Search_all_top_treatments__Category", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 3 | adaptable_train_0006::ep003 | adaptable:b55d97bdd73158d55c5c4ce2 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Charles from USA Termites and traditional harvest and fashioning.\n[Do you talk with your friends and audience about how a didj is made?] =",
"target... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Rik Van Luijn from Netherlands I let them look in to the bottom of an originally termite hollowed didj and one that was drilled out by a ... | [
"Apply the learned table pattern for a table task. Predict [Do you talk with your friends and audience about how a didj is made?] for the row.\n[Name and Country] Scott from Australia Find the stick you want and put it on a termites nest until ready then decorate\n[Do you talk with your friends and audience about h... | 1 | 0 | 3 | 1 | null | b55d97bdd73158d55c5c4ce2 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster26.parquet", "source_item_id": "b55d97bdd73158d55c5c4ce2", "source_rows": 103, "source_task_id": "ba0586f5_finest_online_didgeridoo_store__ence_about_how_a_didj_is_made_", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 4 | adaptable_train_0006::ep004 | adaptable:4bfd4abc1844e1765ff54e80 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Last Poster] for the row.\n[Topic — Add New »] Timberland Pas cher différents choix de formateur que l' [Posts] 1 [Freshness] 2 years [Last Poster]\n[Last Poster] =",
"target": "dongtingqiu",
"candidates": [
"dongtingqiu",
"dudedah"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Last Poster] for the row.\n[Topic — Add New »] Toms sale creature has the rich emotional life [Posts] 2 [Freshness] 2 years [Last Poster]\n[Last Poster] =",
"target": "shenjie",
"candidates": [
"dongtingqiu",
"dudedah",
... | [
"Apply the learned table pattern for a table task. Predict [Last Poster] for the row.\n[Topic — Add New »] The taxi was late.txt [Posts] 1 [Freshness] 2 years [Last Poster]\n[Last Poster] =",
"Apply the learned table pattern for a table task. Predict [Last Poster] for the row.\n[Topic — Add New »] Toms sale think... | 0 | 0 | 1 | 1 | null | 4bfd4abc1844e1765ff54e80 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "4bfd4abc1844e1765ff54e80", "source_rows": 30, "source_task_id": "4cae3cfe_Moots_Forum__Last_Poster", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 5 | adaptable_train_0006::ep005 | adaptable:4e04babc8e3d3436f61b4313 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Name] Frosa [Type]\n[Type] =",
"target": "Character",
"candidates": [
"Character",
"Concept",
"Game",
"Thing",
"User"
],
"source": "UnpredicTable",
"source_id": "a20e4262_bobafettjm... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] beachthunder [Type]\n[Type] =",
"target": "User",
"candidates": [
"Character",
"Concept",
"Game",
"Thing",
"User"
],
"source": "UnpredicTable",
"source_id": "a20e4... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] peezmachine [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] jagged85 [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\... | 0.5 | 1 | 2 | 1 | null | 4e04babc8e3d3436f61b4313 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 5, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "4e04babc8e3d3436f61b4313", "source_rows": 50, "source_task_id": "a20e4262_bobafettjm_s_Following_List__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 6 | adaptable_train_0006::ep006 | adaptable:4e04babc8e3d3436f61b4313 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Name] Frosa [Type]\n[Type] =",
"target": "Character",
"candidates": [
"Character",
"Concept",
"Game",
"Thing",
"User"
],
"source": "UnpredicTable",
"source_id": "a20e4262_bobafettjm_s_F... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] beachthunder [Type]\n[Type] =",
"target": "User",
"candidates": [
"Character",
"Concept",
"Game",
"Thing",
"User"
],
"source": "UnpredicTable",
"source_id": "a20e4... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] peezmachine [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Name] jagged85 [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\... | 0.5 | 0 | 2 | 1 | null | 4e04babc8e3d3436f61b4313 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "4e04babc8e3d3436f61b4313", "source_rows": 50, "source_task_id": "a20e4262_bobafettjm_s_Following_List__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0006 | 254,482,665 | null | null | 7 | adaptable_train_0006::ep007 | adaptable:efca3e45b9264eac5b9cadda | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [1] for the row.\n[0] Review [1]\n[1] =",
"target": "Article",
"candidates": [
"Article",
"Test",
"Video"
],
"source": "UnpredicTable",
"source_id": "0f57ace9_ROSS_CiRCUIT_by_Octane_Fitness__1",
"metadata_json":... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] The Octane Story [1]\n[1] =",
"target": "Article",
"candidates": [
"Article",
"Test",
"Video"
],
"source": "UnpredicTable",
"source_id": "0f57ace9_ROSS_CiRCUIT_by_Octane_Fitness__1"... | [
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] Workout Boosters [1]\n[1] =",
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] White Pages [1]\n[1] =",
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] Marketing [1]\... | 0 | 0 | 1 | 1 | null | efca3e45b9264eac5b9cadda | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster24.parquet", "source_item_id": "efca3e45b9264eac5b9cadda", "source_rows": 32, "source_task_id": "0f57ace9_ROSS_CiRCUIT_by_Octane_Fitness__1", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 0 | adaptable_train_0007::ep000 | adaptable:b6f811d780d8ff92a4b52b4e | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Ranged Accuracy] for the row.\n[Name] Squid Sushi [Lvl] -- [Slot] Inventory [Type] Food [Jobs] All [Ranged Accuracy]\n[Ranged Accuracy] =",
"target": "+15%",
"candidates": [
"+15%",
"+16%",
"+17%",
"+19%",
"+7%",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Ranged Accuracy] for the row.\n[Name] Fatty Tuna Sushi [Lvl] -- [Slot] Inventory [Type] Food [Jobs] All [Ranged Accuracy]\n[Ranged Accuracy] =",
"target": "+16%",
"candidates": [
"+15%",
"+16%",
"+17%",
"+19%... | [
"Apply the learned table pattern for a table task. Predict [Ranged Accuracy] for the row.\n[Name] Timbre Timbers Taco [Lvl] -- [Slot] Inventory [Type] Food [Jobs] All [Ranged Accuracy]\n[Ranged Accuracy] =",
"Apply the learned table pattern for a table task. Predict [Ranged Accuracy] for the row.\n[Name] Timbre T... | 0 | 0 | 1 | 1 | null | b6f811d780d8ff92a4b52b4e | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "b6f811d780d8ff92a4b52b4e", "source_rows": 30, "source_task_id": "abd696ff_inal_Fantasy_XI___somepage_com__Ranged_Accuracy", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 1 | adaptable_train_0007::ep001 | adaptable:6b7e83f1da7e916f1acf88eb | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Priority] for the row.\n[Ticket] #689 [Summary] Add subs selection to featured video [Status] closed [Type] task [Milestone] 4.3.1 [Component] VideoPlayer [Priority]\n[Priority] =",
"target": "blocker",
"candidates": [
"blocker",
"c... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Priority] for the row.\n[Ticket] #606 [Summary] Add Hong Kong to list of countries [Status] closed [Type] task [Milestone] 4.3.1 [Component] Architecture [Priority]\n[Priority] =",
"target": "major",
"candidates": [
"blocker",... | [
"Apply the learned table pattern for a table task. Predict [Priority] for the row.\n[Ticket] #641 [Summary] Update collective.piwik.flowplayer to use the latest piwik version [Status] closed [Type] task [Milestone] 4.3.1 [Component] Architecture [Priority]\n[Priority] =",
"Apply the learned table pattern for a ta... | 0 | 0 | 1 | 1 | null | 6b7e83f1da7e916f1acf88eb | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "6b7e83f1da7e916f1acf88eb", "source_rows": 28, "source_task_id": "5844371e_y_milestone_descending___Plumi__Priority", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 2 | adaptable_train_0007::ep002 | adaptable:d58afb9ce0344e26235e976a | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Information technology [DEGREE] BE [INTAKE] 120 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Full time",
"candidates": [
"Full time",
"Part time"
],
"source": "Unp... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Chemical engineering [DEGREE] BE [INTAKE] 13 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Part time",
"candidates": [
"Full time",
"Part time"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Power system engineering [DEGREE] BE [INTAKE] 18 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Water r... | 1 | 2 | 3 | 1 | null | d58afb9ce0344e26235e976a | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster13.parquet", "source_item_id": "d58afb9ce0344e26235e976a", "source_rows": 31, "source_task_id": "acdae772_NNAMALAI_NAGAR___ExamCrazy_com__NATURE", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 3 | adaptable_train_0007::ep003 | adaptable:6e97dc806b049424a485101b | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Resource Type] for the row.\n[Title] Retrofit of heat exchangers to haemodialysis machines Green Nephrology Programme [Publication date] 01/2010 [Resource Type]\n[Resource Type] =",
"target": "case study",
"candidates": [
"case study",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[Title] Green Nephrology Award entries 2012 - posters G-N Green Nephrology Programme [Publication date] 09/2012 [Resource Type]\n[Resource Type] =",
"target": "case study",
"candidates": [
"case st... | [
"Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[Title] Green Nephrology Green Stars Guide Green Nephrology Programme [Publication date] 09/2010 [Resource Type]\n[Resource Type] =",
"Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[T... | 0.5 | 1 | 2 | 1 | null | 6e97dc806b049424a485101b | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "6e97dc806b049424a485101b", "source_rows": 46, "source_task_id": "0befcddc_tre_for_Sustainable_Healthcare__Resource_Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 4 | adaptable_train_0007::ep004 | adaptable:d58afb9ce0344e26235e976a | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Information technology [DEGREE] BE [INTAKE] 120 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Full time",
"candidates": [
"Full time",
"Part time"
],
"source": "Unpredi... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Chemical engineering [DEGREE] BE [INTAKE] 13 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Part time",
"candidates": [
"Full time",
"Part time"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Power system engineering [DEGREE] BE [INTAKE] 18 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Water r... | 1 | 1 | 3 | 1 | null | d58afb9ce0344e26235e976a | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster13.parquet", "source_item_id": "d58afb9ce0344e26235e976a", "source_rows": 31, "source_task_id": "acdae772_NNAMALAI_NAGAR___ExamCrazy_com__NATURE", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 5 | adaptable_train_0007::ep005 | adaptable:6e97dc806b049424a485101b | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Resource Type] for the row.\n[Title] Retrofit of heat exchangers to haemodialysis machines Green Nephrology Programme [Publication date] 01/2010 [Resource Type]\n[Resource Type] =",
"target": "case study",
"candidates": [
"case study",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[Title] Green Nephrology Award entries 2012 - posters G-N Green Nephrology Programme [Publication date] 09/2012 [Resource Type]\n[Resource Type] =",
"target": "case study",
"candidates": [
"case st... | [
"Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[Title] Green Nephrology Green Stars Guide Green Nephrology Programme [Publication date] 09/2010 [Resource Type]\n[Resource Type] =",
"Apply the learned table pattern for a table task. Predict [Resource Type] for the row.\n[T... | 0.5 | 0 | 2 | 1 | null | 6e97dc806b049424a485101b | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "6e97dc806b049424a485101b", "source_rows": 46, "source_task_id": "0befcddc_tre_for_Sustainable_Healthcare__Resource_Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 6 | adaptable_train_0007::ep006 | adaptable:d58afb9ce0344e26235e976a | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Information technology [DEGREE] BE [INTAKE] 120 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Full time",
"candidates": [
"Full time",
"Part time"
],
"source": "Unpredi... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Chemical engineering [DEGREE] BE [INTAKE] 13 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"target": "Part time",
"candidates": [
"Full time",
"Part time"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Power system engineering [DEGREE] BE [INTAKE] 18 [ACCREDITION] No accredition [NATURE]\n[NATURE] =",
"Apply the learned table pattern for a table task. Predict [NATURE] for the row.\n[NAME OF THE COURSE] Water r... | 1 | 0 | 3 | 1 | null | d58afb9ce0344e26235e976a | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster13.parquet", "source_item_id": "d58afb9ce0344e26235e976a", "source_rows": 31, "source_task_id": "acdae772_NNAMALAI_NAGAR___ExamCrazy_com__NATURE", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0007 | 835,461,987 | null | null | 7 | adaptable_train_0007::ep007 | adaptable:05879ff1823680b3ea61544d | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Lamp Type] for the row.\n[File Name] DF12-VFL-400H.IES [Wattage] 400W [Description] Vertical Flood [Lamp Type]\n[Lamp Type] =",
"target": "High Pressure Sodium",
"candidates": [
"High Pressure Sodium",
"MasterColor Elite",
"Me... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Lamp Type] for the row.\n[File Name] DF12-HSP-400X.IES [Wattage] 400W [Description] Horizontal Spot [Lamp Type]\n[Lamp Type] =",
"target": "Metal Halide - Coated",
"candidates": [
"High Pressure Sodium",
"MasterColor Eli... | [
"Apply the learned table pattern for a table task. Predict [Lamp Type] for the row.\n[File Name] DF12-VFL-315MCE.IES [Wattage] 315W [Description] Vertical Flood [Lamp Type]\n[Lamp Type] =",
"Apply the learned table pattern for a table task. Predict [Lamp Type] for the row.\n[File Name] DF12-HSP-400P-L.IES [Wattag... | 0 | 0 | 1 | 1 | null | 05879ff1823680b3ea61544d | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "05879ff1823680b3ea61544d", "source_rows": 59, "source_task_id": "1a2564e3_ral_Outdoor_Lighting_Solutions__Lamp_Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 0 | adaptable_train_0008::ep000 | adaptable:fb64a5a814f9143d7caa4a66 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Award] for the row.\n[Organization] BGC of Coastal Carolina [Category] Advertising [Year] 2011 [Award]\n[Award] =",
"target": "Bronze",
"candidates": [
"Bronze",
"Gold",
"Silver"
],
"source": "UnpredicTable",
"sour... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Award] for the row.\n[Organization] BGC of Henderson County [Category] Comprehensive Marketing Strategy [Year] 2011 [Award]\n[Award] =",
"target": "Gold",
"candidates": [
"Bronze",
"Gold",
"Silver"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [Award] for the row.\n[Organization] BGC of Henderson County [Category] Comprehensive Marketing Strategy [Year] 2012 [Award]\n[Award] =",
"Apply the learned table pattern for a table task. Predict [Award] for the row.\n[Organization] TSA BGC of High Point... | 0 | 0 | 1 | 1 | null | fb64a5a814f9143d7caa4a66 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "fb64a5a814f9143d7caa4a66", "source_rows": 50, "source_task_id": "f404b6bc__Girls_Clubs_of_North_Carolina__Award", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 1 | adaptable_train_0008::ep001 | adaptable:08e58752c38c0863f1426cb7 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Exam Method] for the row.\n[Classification Title] Administrative Assistant II [Exam Type] Written [Exam Method]\n[Exam Method] =",
"target": "In Person",
"candidates": [
"In Person",
"Online"
],
"source": "UnpredicTable",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Title] Staff Services Manager I [Exam Type] Qualifications Assessment [Exam Method]\n[Exam Method] =",
"target": "Online",
"candidates": [
"In Person",
"Online"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Title] Accountant I (Specialist) [Exam Type] Qualifications Assessment [Exam Method]\n[Exam Method] =",
"Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Titl... | 0.5 | 1 | 2 | 1 | null | 08e58752c38c0863f1426cb7 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "08e58752c38c0863f1426cb7", "source_rows": 43, "source_task_id": "98a011ee_Opportunities_and_Examinations__Exam_Method", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 2 | adaptable_train_0008::ep002 | adaptable:0c17afb94bfea24979dd2918 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Latvian airplay charts [Sijoitus] No. 4 [Single]\n[Single] =",
"target": "About a Girl",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire",
"The Man Who Sold the W... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Mainstream Rock Tracks (US) [Sijoitus] No. 12 [Single]\n[Single] =",
"target": "The Man Who Sold the World",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire... | [
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Official French Singles Chart [Sijoitus] No. 23 [Single]\n[Single] =",
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Canadian National Airplay Charts [Sij... | 1 | 2 | 3 | 1 | null | 0c17afb94bfea24979dd2918 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster25.parquet", "source_item_id": "0c17afb94bfea24979dd2918", "source_rows": 25, "source_task_id": "0ca91394_lugged_in_New_York___Wikipedia__Single", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 3 | adaptable_train_0008::ep003 | adaptable:75bda90beaf9c8f64fffaba6 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [1] for the row.\n[0] Adaptive Style [2] Crusader, Swordsage, or Warblade level 1st [1]\n[1] =",
"target": "Combat",
"candidates": [
"Combat",
"Divine",
"General",
"Item Creation",
"Psionic",
"Tactical",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] Blade Meditation [2] BAB +4, 1 Martial maneuver [1]\n[1] =",
"target": "Combat",
"candidates": [
"Combat",
"Divine",
"General",
"Item Creation",
"Psionic",
"Tactical",
"... | [
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] Gloom Razor [2] BAB +6, Shadow Blade, Stealth 6 ranks, 2 Shadow Hand maneuvers [1]\n[1] =",
"Apply the learned table pattern for a table task. Predict [1] for the row.\n[0] Instant Clarity [2] Manifester level 4th [1]\n[1] =",
"App... | 0 | 0 | 1 | 1 | null | 75bda90beaf9c8f64fffaba6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "75bda90beaf9c8f64fffaba6", "source_rows": 39, "source_task_id": "1af89297__of_Darkness___Obsidian_Portal__1", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 4 | adaptable_train_0008::ep004 | adaptable:0c17afb94bfea24979dd2918 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Latvian airplay charts [Sijoitus] No. 4 [Single]\n[Single] =",
"target": "About a Girl",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire",
"The Man Who Sold the World... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Mainstream Rock Tracks (US) [Sijoitus] No. 12 [Single]\n[Single] =",
"target": "The Man Who Sold the World",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire... | [
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Official French Singles Chart [Sijoitus] No. 23 [Single]\n[Single] =",
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Canadian National Airplay Charts [Sij... | 1 | 1 | 3 | 1 | null | 0c17afb94bfea24979dd2918 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster25.parquet", "source_item_id": "0c17afb94bfea24979dd2918", "source_rows": 25, "source_task_id": "0ca91394_lugged_in_New_York___Wikipedia__Single", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 5 | adaptable_train_0008::ep005 | adaptable:08e58752c38c0863f1426cb7 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Exam Method] for the row.\n[Classification Title] Administrative Assistant II [Exam Type] Written [Exam Method]\n[Exam Method] =",
"target": "In Person",
"candidates": [
"In Person",
"Online"
],
"source": "UnpredicTable",
"s... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Title] Staff Services Manager I [Exam Type] Qualifications Assessment [Exam Method]\n[Exam Method] =",
"target": "Online",
"candidates": [
"In Person",
"Online"
],
"sour... | [
"Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Title] Accountant I (Specialist) [Exam Type] Qualifications Assessment [Exam Method]\n[Exam Method] =",
"Apply the learned table pattern for a table task. Predict [Exam Method] for the row.\n[Classification Titl... | 0.5 | 0 | 2 | 1 | null | 08e58752c38c0863f1426cb7 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "08e58752c38c0863f1426cb7", "source_rows": 43, "source_task_id": "98a011ee_Opportunities_and_Examinations__Exam_Method", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 6 | adaptable_train_0008::ep006 | adaptable:0c17afb94bfea24979dd2918 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Latvian airplay charts [Sijoitus] No. 4 [Single]\n[Single] =",
"target": "About a Girl",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire",
"The Man Who Sold the World... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Mainstream Rock Tracks (US) [Sijoitus] No. 12 [Single]\n[Single] =",
"target": "The Man Who Sold the World",
"candidates": [
"About a Girl",
"All Apologies",
"Lake of Fire... | [
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1994 [Lista] Official French Singles Chart [Sijoitus] No. 23 [Single]\n[Single] =",
"Apply the learned table pattern for a table task. Predict [Single] for the row.\n[Vuosi] 1995 [Lista] Canadian National Airplay Charts [Sij... | 1 | 0 | 3 | 1 | null | 0c17afb94bfea24979dd2918 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster25.parquet", "source_item_id": "0c17afb94bfea24979dd2918", "source_rows": 25, "source_task_id": "0ca91394_lugged_in_New_York___Wikipedia__Single", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0008 | 842,257,053 | null | null | 7 | adaptable_train_0008::ep007 | adaptable:0e1ebc3678691d1e35337d61 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Priority] for the row.\n[Bug #] 777171 [Title] Percent signs in the wiki field break summit [Priority]\n[Priority] =",
"target": "Critical",
"candidates": [
"Critical",
"High",
"Low",
"Medium",
"Undecided",
"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Priority] for the row.\n[Bug #] 793018 [Title] Pull the summary from the launchpad blueprint and push it out via the iCal to Guidebook [Priority]\n[Priority] =",
"target": "High",
"candidates": [
"Critical",
"High",
... | [
"Apply the learned table pattern for a table task. Predict [Priority] for the row.\n[Bug #] 779833 [Title] Automatically clear cache when the data it contains changes [Priority]\n[Priority] =",
"Apply the learned table pattern for a table task. Predict [Priority] for the row.\n[Bug #] 849331 [Title] Needs to send... | 0 | 0 | 1 | 1 | null | 0e1ebc3678691d1e35337d61 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "0e1ebc3678691d1e35337d61", "source_rows": 36, "source_task_id": "7468ca37_velopment_Cycle___Michael_Hall__Priority", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 0 | adaptable_train_0009::ep000 | adaptable:d5b9c30e37d64a60116987ae | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Ticket] #12265 [Summary] Media (js/css) collection strategy in Forms has no order dependence concept [Status] new [Owner] nobody [Version] 1.1 [Severity] Normal [Type]\n[Type] =",
"target": "Bug",
"candidates": [
"Bug... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #15574 [Summary] IndexError: list index out of range caused by inline formsets [Status] new [Owner] nobody [Version] master [Severity] Normal [Type]\n[Type] =",
"target": "Bug",
"candidates": [
"Bu... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #22654 [Summary] DecimalField and DECIMAL_SEPARATOR (in admin) [Status] new [Version] 1.6 [Severity] Normal [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #18830 [S... | 0.5 | 1 | 2 | 1 | null | d5b9c30e37d64a60116987ae | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "d5b9c30e37d64a60116987ae", "source_rows": 79, "source_task_id": "8aed8525_Custom_Query___Django__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 1 | adaptable_train_0009::ep001 | adaptable:13f09e51186a41c2c572512d | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Element] for the row.\n[Name] Sapphron [Stats] Strong Speed, Strong Element Attack & Defense [Area] Somewhere in the Cave of Mist (Not found yet) [Element]\n[Element] =",
"target": "Earth",
"candidates": [
"Earth",
"Fire",
"Li... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Element] for the row.\n[Name] Sledgehog [Stats] Random Health, Strong Element Attack & Defense [Area] Rocks in Cave of Mist [Element]\n[Element] =",
"target": "Earth",
"candidates": [
"Earth",
"Fire",
"Lightning",
... | [
"Apply the learned table pattern for a table task. Predict [Element] for the row.\n[Name] Treemur [Stats] Strong Element Attack & Defense [Area] Arena, The Beach [Element]\n[Element] =",
"Apply the learned table pattern for a table task. Predict [Element] for the row.\n[Name] Squibee [Stats] High Element Attack &... | 0 | 0 | 1 | 1 | null | 13f09e51186a41c2c572512d | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "13f09e51186a41c2c572512d", "source_rows": 48, "source_task_id": "3db66862_Monster___Miscrits__Wiki__Element", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 2 | adaptable_train_0009::ep002 | adaptable:a8c9c3e34df8e9cac9780489 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Area] for the row.\n[Page] amtterm [Kurzbeschreibung] Serial-over-lan (sol) client for Intel AMT, console version [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
],
"source"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] apache-perl [Kurzbeschreibung] versatile, high-performance HTTP server with Perl support [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
]... | [
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] awstats [Kurzbeschreibung] powerful and featureful web server log analyzer [Area]\n[Area] =",
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] adduser-ng-doc [Kurzbeschreibung] Documentatio... | 1 | 2 | 3 | 1 | null | a8c9c3e34df8e9cac9780489 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster15.parquet", "source_item_id": "a8c9c3e34df8e9cac9780489", "source_rows": 50, "source_task_id": "8e9df9e0_ebian__Suchergebnisse_für_Perl__Area", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 3 | adaptable_train_0009::ep003 | adaptable:d5b9c30e37d64a60116987ae | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Ticket] #12265 [Summary] Media (js/css) collection strategy in Forms has no order dependence concept [Status] new [Owner] nobody [Version] 1.1 [Severity] Normal [Type]\n[Type] =",
"target": "Bug",
"candidates": [
"Bug",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #15574 [Summary] IndexError: list index out of range caused by inline formsets [Status] new [Owner] nobody [Version] master [Severity] Normal [Type]\n[Type] =",
"target": "Bug",
"candidates": [
"Bu... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #22654 [Summary] DecimalField and DECIMAL_SEPARATOR (in admin) [Status] new [Version] 1.6 [Severity] Normal [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #18830 [S... | 0.5 | 0 | 2 | 1 | null | d5b9c30e37d64a60116987ae | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "d5b9c30e37d64a60116987ae", "source_rows": 79, "source_task_id": "8aed8525_Custom_Query___Django__Type", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 4 | adaptable_train_0009::ep004 | adaptable:3638c6b9b60c6ec092515165 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] AIBD/EUROVISION ACADEMY/CCTV Master Class: Shooting Video Content with a Smart Phone or Tablet [Author] geraldine [Views today] 2,379 [Type]\n[Type] =",
"target": "Event",
"candidates": [
"Event",
"Image"... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] AIBD/ITU/ABU Workshop on Enhancing Digital Terrestrial Television Broadcasting Transition Experience [Author] geraldine [Views today] 2,304 [Type]\n[Type] =",
"target": "Event",
"candidates": [
"Eve... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Story telling Techniques [Author] geraldine [Views today] 2,297 [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] AIBD at Broadcast Asia 2015 [Author] rabi [Views today]... | 0 | 0 | 1 | 1 | null | 3638c6b9b60c6ec092515165 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "3638c6b9b60c6ec092515165", "source_rows": 25, "source_task_id": "b1668d13_e_for_Broadcasting_Development__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 5 | adaptable_train_0009::ep005 | adaptable:a8c9c3e34df8e9cac9780489 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Area] for the row.\n[Page] amtterm [Kurzbeschreibung] Serial-over-lan (sol) client for Intel AMT, console version [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
],
"source": "U... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] apache-perl [Kurzbeschreibung] versatile, high-performance HTTP server with Perl support [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
]... | [
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] awstats [Kurzbeschreibung] powerful and featureful web server log analyzer [Area]\n[Area] =",
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] adduser-ng-doc [Kurzbeschreibung] Documentatio... | 1 | 1 | 3 | 1 | null | a8c9c3e34df8e9cac9780489 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 5, "slot_role": "recurrence", "source_file": "unpredictable_cluster15.parquet", "source_item_id": "a8c9c3e34df8e9cac9780489", "source_rows": 50, "source_task_id": "8e9df9e0_ebian__Suchergebnisse_für_Perl__Area", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 6 | adaptable_train_0009::ep006 | adaptable:a8c9c3e34df8e9cac9780489 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Area] for the row.\n[Page] amtterm [Kurzbeschreibung] Serial-over-lan (sol) client for Intel AMT, console version [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
],
"source": "U... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] apache-perl [Kurzbeschreibung] versatile, high-performance HTTP server with Perl support [Area]\n[Area] =",
"target": "Debianpaket",
"candidates": [
"Debianpaket",
"Link",
"Projekt"
]... | [
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] awstats [Kurzbeschreibung] powerful and featureful web server log analyzer [Area]\n[Area] =",
"Apply the learned table pattern for a table task. Predict [Area] for the row.\n[Page] adduser-ng-doc [Kurzbeschreibung] Documentatio... | 1 | 0 | 3 | 1 | null | a8c9c3e34df8e9cac9780489 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "recurrence", "source_file": "unpredictable_cluster15.parquet", "source_item_id": "a8c9c3e34df8e9cac9780489", "source_rows": 50, "source_task_id": "8e9df9e0_ebian__Suchergebnisse_für_Perl__Area", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0009 | 4,236,302,544 | null | null | 7 | adaptable_train_0009::ep007 | adaptable:666f9c719df687681ba13eea | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Destinations] for the row.\n[Common Name] Locust Leafminer [Scientific Name] Odontota dorsalis [Destinations]\n[Destinations] =",
"target": "Info",
"candidates": [
"Info",
"Info Maps"
],
"source": "UnpredicTable",
"sourc... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Destinations] for the row.\n[Common Name] Cactus Moth [Scientific Name] Cactoblastis cactorum [Destinations]\n[Destinations] =",
"target": "Info Maps",
"candidates": [
"Info",
"Info Maps"
],
"source": "UnpredicTa... | [
"Apply the learned table pattern for a table task. Predict [Destinations] for the row.\n[Common Name] European Elm Bark Beetle [Scientific Name] Scolytus scolytus [Destinations]\n[Destinations] =",
"Apply the learned table pattern for a table task. Predict [Destinations] for the row.\n[Common Name] Olive Fruit Fl... | 0 | 0 | 1 | 1 | null | 666f9c719df687681ba13eea | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster18.parquet", "source_item_id": "666f9c719df687681ba13eea", "source_rows": 624, "source_task_id": "ab59a284___Pest_Tracker___CAPS_Services__Destinations", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 0 | adaptable_train_0010::ep000 | adaptable:759a6bc537894e78659e40f9 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Level] for the row.\n[UoS Code] ACCT6002 [Name] International Accounting - (Stream A) [Faculty] Business (Business School) [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Postgraduate",
"candidates": [
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ENGL1011 [Name] Introduction to Film Studies - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Undergraduate",
"candid... | [
"Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ARIN6904 [Name] Mobile Media and Games - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"Apply the learned table pattern for a table task. Predict [Le... | 1 | 2 | 3 | 1 | null | 759a6bc537894e78659e40f9 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "759a6bc537894e78659e40f9", "source_rows": 40, "source_task_id": "d91a7c06_ool___The_University_of_Sydney__Level", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 1 | adaptable_train_0010::ep001 | adaptable:759a6bc537894e78659e40f9 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Level] for the row.\n[UoS Code] ACCT6002 [Name] International Accounting - (Stream A) [Faculty] Business (Business School) [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Postgraduate",
"candidates": [
"Pos... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ENGL1011 [Name] Introduction to Film Studies - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Undergraduate",
"candid... | [
"Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ARIN6904 [Name] Mobile Media and Games - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"Apply the learned table pattern for a table task. Predict [Le... | 1 | 1 | 3 | 1 | null | 759a6bc537894e78659e40f9 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "759a6bc537894e78659e40f9", "source_rows": 40, "source_task_id": "d91a7c06_ool___The_University_of_Sydney__Level", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 2 | adaptable_train_0010::ep002 | adaptable:759a6bc537894e78659e40f9 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Level] for the row.\n[UoS Code] ACCT6002 [Name] International Accounting - (Stream A) [Faculty] Business (Business School) [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Postgraduate",
"candidates": [
"Pos... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ENGL1011 [Name] Introduction to Film Studies - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"target": "Undergraduate",
"candid... | [
"Apply the learned table pattern for a table task. Predict [Level] for the row.\n[UoS Code] ARIN6904 [Name] Mobile Media and Games - (Stream A) [Faculty] Arts and Social Sciences [4] Please see Details for Class info and Enrolment [Level]\n[Level] =",
"Apply the learned table pattern for a table task. Predict [Le... | 1 | 0 | 3 | 1 | null | 759a6bc537894e78659e40f9 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "recurrence", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "759a6bc537894e78659e40f9", "source_rows": 40, "source_task_id": "d91a7c06_ool___The_University_of_Sydney__Level", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 3 | adaptable_train_0010::ep003 | adaptable:1f25b38acd2b9c5f4d1cdb67 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Log On As] for the row.\n[Service Name] Base Filtering Engine [Startup Type] Automatic [Log On As]\n[Log On As] =",
"target": "Local Service",
"candidates": [
"Local Service",
"Local System",
"Network Service",
"NetworkS... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] Offline Files [Startup Type] Disabled [Log On As]\n[Log On As] =",
"target": "Local System",
"candidates": [
"Local Service",
"Local System",
"Network Service",
"Networ... | [
"Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] WebClient [Startup Type] Manual [Log On As]\n[Log On As] =",
"Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] Superfetch [Startup Type] Automatic [Log On As]\n[Log... | 0.5 | 1 | 2 | 1 | null | 1f25b38acd2b9c5f4d1cdb67 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "new", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "1f25b38acd2b9c5f4d1cdb67", "source_rows": 145, "source_task_id": "71422c8d_count___The_Winhelponline_Blog__Log_On_As", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 4 | adaptable_train_0010::ep004 | adaptable:1f25b38acd2b9c5f4d1cdb67 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Log On As] for the row.\n[Service Name] Base Filtering Engine [Startup Type] Automatic [Log On As]\n[Log On As] =",
"target": "Local Service",
"candidates": [
"Local Service",
"Local System",
"Network Service",
"NetworkServi... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] Offline Files [Startup Type] Disabled [Log On As]\n[Log On As] =",
"target": "Local System",
"candidates": [
"Local Service",
"Local System",
"Network Service",
"Networ... | [
"Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] WebClient [Startup Type] Manual [Log On As]\n[Log On As] =",
"Apply the learned table pattern for a table task. Predict [Log On As] for the row.\n[Service Name] Superfetch [Startup Type] Automatic [Log On As]\n[Log... | 0.5 | 0 | 2 | 1 | null | 1f25b38acd2b9c5f4d1cdb67 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "1f25b38acd2b9c5f4d1cdb67", "source_rows": 145, "source_task_id": "71422c8d_count___The_Winhelponline_Blog__Log_On_As", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 5 | adaptable_train_0010::ep005 | adaptable:81c0f3f4067cafc1da968955 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] Breaks with the same image in 2 fields with different image styles [Author] rudiedirkx [Replies] 3 [Last updated] 2 hours 17 min ago [Type]\n[Type] =",
"target": "Issue",
"candidates": [
"Issue",
"Release... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] External apps do not install - \"Cannot extract temporary://..., not a valid archive\" [Author] Friedebarth [Replies] 0 [Last updated] 2 hours 26 min ago [Type]\n[Type] =",
"target": "Issue",
"candidates"... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Rewrite EntityManagerTest to use phpspec/prophecy [Author] tim.plunkett [Replies] 4 [Last updated] 2 hours 12 min ago [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] A... | 0 | 0 | 1 | 1 | null | 81c0f3f4067cafc1da968955 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "81c0f3f4067cafc1da968955", "source_rows": 24, "source_task_id": "0c286e09_Recent_content___Drupal_org__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 6 | adaptable_train_0010::ep006 | adaptable:8590316eb9f3d45892ad671c | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Self-Use] for the row.\n[Core] Sanger Sequencing [Software] Sequencher 3.1.1 [Self-Use]\n[Self-Use] =",
"target": "No",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
"source_id": "51a772f9_search___University... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Self-Use] for the row.\n[Core] Cytometry [Software] FACS Diva 6.1 and FACS Diva 8 [Self-Use]\n[Self-Use] =",
"target": "Yes",
"candidates": [
"No",
"Yes"
],
"source": "UnpredicTable",
"source_id": "51a772f9_s... | [
"Apply the learned table pattern for a table task. Predict [Self-Use] for the row.\n[Core] Bioinformatics [Software] Genome Bioinformatics [Self-Use]\n[Self-Use] =",
"Apply the learned table pattern for a table task. Predict [Self-Use] for the row.\n[Core] Bioinformatics [Software] MethylMapper [Self-Use]\n[Self-... | 0 | 0 | 1 | 1 | null | 8590316eb9f3d45892ad671c | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "8590316eb9f3d45892ad671c", "source_rows": 36, "source_task_id": "51a772f9_search___University_of_Florida__Self_Use", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0010 | 1,882,124,620 | null | null | 7 | adaptable_train_0010::ep007 | adaptable:90c5b3e1659d81591e0cf3e8 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Category] for the row.\n[Term] Gigabyte [Category]\n[Category] =",
"target": "Bits and Bytes",
"candidates": [
"Bits and Bytes",
"File Formats",
"Hardware",
"Internet",
"Software",
"Technical"
],
"sou... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Term] Boot [Category]\n[Category] =",
"target": "Technical",
"candidates": [
"Bits and Bytes",
"File Formats",
"Hardware",
"Internet",
"Software",
"Technical"
],
"... | [
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Term] Download [Category]\n[Category] =",
"Apply the learned table pattern for a table task. Predict [Category] for the row.\n[Term] DSL [Category]\n[Category] =",
"Apply the learned table pattern for a table task. Predict [Cat... | 0 | 0 | 1 | 1 | null | 90c5b3e1659d81591e0cf3e8 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "90c5b3e1659d81591e0cf3e8", "source_rows": 78, "source_task_id": "77ba1e0f__Terms_with_a_Tech_Factor_of_2__Category", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 0 | adaptable_train_0011::ep000 | adaptable:12c7b04d1b15cdf750624d98 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Variable] MOUSE_EMULATE_3_BUTTONS_ENABLED [Type]\n[Type] =",
"target": "boolean",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin_Client_... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] RDP_DOMAIN [Abbreviation] rd [Type]\n[Type] =",
"target": "string",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] X_FONT_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] XDM_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predic... | 1 | 2 | 3 | 1 | null | 12c7b04d1b15cdf750624d98 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "12c7b04d1b15cdf750624d98", "source_rows": 72, "source_task_id": "f94b8c05_hin_Client__Version_0_6_Readme__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 1 | adaptable_train_0011::ep001 | adaptable:08791a908981986941616bb6 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Rarity] for the row.\n[Name] Toe Jammer [Incubation] 00:02:00 [Type] Water [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"target": "Common",
"candidates": [
"Common",
"Legendary Rarity",
"Limited",
"Rare"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] Jeeode [Incubation] 36:00:00 [Type] Etherealshard [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"target": "Rare",
"candidates": [
"Common",
"Legendary Rarity",
"Limited",
... | [
"Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] PomPom [Incubation] 12:00:00 [Type] Air, Cold, Earth [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] Dragong [Incubation] 42:00:00... | 0.5 | 1 | 2 | 1 | null | 08791a908981986941616bb6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "08791a908981986941616bb6", "source_rows": 61, "source_task_id": "7c548d58___My_Singing_Monsters_Breeding__Rarity", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 2 | adaptable_train_0011::ep002 | adaptable:67a4c79ab541c59a3da88f11 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Used] for the row.\n[Key] C-F11 [For] Clock in a task (show menu with prefix) [Used]\n[Used] =",
"target": "Often",
"candidates": [
"Often",
"Rare",
"Sometimes",
"Very Often"
],
"source": "UnpredicTable",
"so... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Used] for the row.\n[Key] C-f9 [For] Previous buffer [Used]\n[Used] =",
"target": "Sometimes",
"candidates": [
"Often",
"Rare",
"Sometimes",
"Very Often"
],
"source": "UnpredicTable",
"source_id":... | [
"Apply the learned table pattern for a table task. Predict [Used] for the row.\n[Key] f9 i [For] Info manual [Used]\n[Used] =",
"Apply the learned table pattern for a table task. Predict [Used] for the row.\n[Key] f9 v [For] Toggle visible mode (for showing/editing links) [Used]\n[Used] =",
"Apply the learned t... | 0 | 0 | 1 | 1 | null | 67a4c79ab541c59a3da88f11 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "67a4c79ab541c59a3da88f11", "source_rows": 29, "source_task_id": "9256621a_anize_Your_Life_In_Plain_Text___Used", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 3 | adaptable_train_0011::ep003 | adaptable:12c7b04d1b15cdf750624d98 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Variable] MOUSE_EMULATE_3_BUTTONS_ENABLED [Type]\n[Type] =",
"target": "boolean",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin_Client__Ver... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] RDP_DOMAIN [Abbreviation] rd [Type]\n[Type] =",
"target": "string",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] X_FONT_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] XDM_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predic... | 1 | 1 | 3 | 1 | null | 12c7b04d1b15cdf750624d98 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "12c7b04d1b15cdf750624d98", "source_rows": 72, "source_task_id": "f94b8c05_hin_Client__Version_0_6_Readme__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 4 | adaptable_train_0011::ep004 | adaptable:08791a908981986941616bb6 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Rarity] for the row.\n[Name] Toe Jammer [Incubation] 00:02:00 [Type] Water [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"target": "Common",
"candidates": [
"Common",
"Legendary Rarity",
"Limited",
"Rare"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] Jeeode [Incubation] 36:00:00 [Type] Etherealshard [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"target": "Rare",
"candidates": [
"Common",
"Legendary Rarity",
"Limited",
... | [
"Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] PomPom [Incubation] 12:00:00 [Type] Air, Cold, Earth [You've Obtained] Login to add [Rarity]\n[Rarity] =",
"Apply the learned table pattern for a table task. Predict [Rarity] for the row.\n[Name] Dragong [Incubation] 42:00:00... | 0.5 | 0 | 2 | 1 | null | 08791a908981986941616bb6 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 4, "slot_role": "recurrence", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "08791a908981986941616bb6", "source_rows": 61, "source_task_id": "7c548d58___My_Singing_Monsters_Breeding__Rarity", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 5 | adaptable_train_0011::ep005 | adaptable:30daf3c7bd7165dc0d08fdd7 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Ticket] #451 [Summary] Copy and Paste Results of Invariant Calculations [Status] new [Priority] major [Component] All Components [Type]\n[Type] =",
"target": "feature",
"candidates": [
"feature",
"task"
],
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #393 [Summary] Path length dependence of transmission through He cell [Status] new [Priority] minor [Milestone] Polarization Reduction [Component] All Components [Type]\n[Type] =",
"target": "task",
"can... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Ticket] #331 [Summary] propagation of errors in USANS reduction [Status] new [Priority] minor [Milestone] Wish List [Component] USANS Reduction [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for ... | 0 | 0 | 1 | 1 | null | 30daf3c7bd7165dc0d08fdd7 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 5, "slot_role": "new", "source_file": "unpredictable_cluster29.parquet", "source_item_id": "30daf3c7bd7165dc0d08fdd7", "source_rows": 30, "source_task_id": "63b626dd_NS_Data_Reduction_and_Analysis__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 6 | adaptable_train_0011::ep006 | adaptable:6d4aa996ec099efe4ecd6209 | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [5] for the row.\n[0] Anthropology [Major] Major [Minor] Minor [Concentration] No [Career Program] No [5]\n[5] =",
"target": "Major Minor No No",
"candidates": [
"Major Minor No No",
"Major No No No",
"No Minor No No",
"N... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [5] for the row.\n[0] Women's and Gender Studies [Major] No [Minor] No [Concentration] Concentration [Career Program] No [5]\n[5] =",
"target": "No No Concentration No",
"candidates": [
"Major Minor No No",
"Major No No N... | [
"Apply the learned table pattern for a table task. Predict [5] for the row.\n[0] Religious Studies [Major] Major [Minor] No [Concentration] No [Career Program] No [5]\n[5] =",
"Apply the learned table pattern for a table task. Predict [5] for the row.\n[0] Accounting [Major] Major [Minor] No [Concentration] No [C... | 0 | 0 | 1 | 1 | null | 6d4aa996ec099efe4ecd6209 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 6, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "6d4aa996ec099efe4ecd6209", "source_rows": 63, "source_task_id": "b33c9ecd_Academic_Programs___Holy_Cross__5", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0011 | 4,113,584,890 | null | null | 7 | adaptable_train_0011::ep007 | adaptable:12c7b04d1b15cdf750624d98 | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [Type] for the row.\n[Variable] MOUSE_EMULATE_3_BUTTONS_ENABLED [Type]\n[Type] =",
"target": "boolean",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin_Client__Ver... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] RDP_DOMAIN [Abbreviation] rd [Type]\n[Type] =",
"target": "string",
"candidates": [
"boolean",
"integer",
"string"
],
"source": "UnpredicTable",
"source_id": "f94b8c05_hin... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] X_FONT_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Variable] XDM_SERVER_NAME [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predic... | 1 | 0 | 3 | 1 | null | 12c7b04d1b15cdf750624d98 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 7, "slot_role": "recurrence", "source_file": "unpredictable_cluster28.parquet", "source_item_id": "12c7b04d1b15cdf750624d98", "source_rows": 72, "source_task_id": "f94b8c05_hin_Client__Version_0_6_Readme__Type", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0012 | 2,400,072,952 | null | null | 0 | adaptable_train_0012::ep000 | adaptable:a2ac8f79e168afd74e41431d | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [2] for the row.\n[0] Trout [1] Mild [2]\n[2] =",
"target": "Delicate",
"candidates": [
"Delicate",
"Delicate-Medium",
"Firm",
"Medium",
"Medium-Firm",
"Texture"
],
"source": "UnpredicTable",
"sour... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Yellowtail [1] Mild [2]\n[2] =",
"target": "Firm",
"candidates": [
"Delicate",
"Delicate-Medium",
"Firm",
"Medium",
"Medium-Firm",
"Texture"
],
"source": "UnpredicTabl... | [
"Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Orange Roughy [1] Mild [2]\n[2] =",
"Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Alaskan Halibut [1] Mild [2]\n[2] =",
"Apply the learned table pattern for a table task. Predict [2] for the row.\... | 1 | 2 | 3 | 1 | null | a2ac8f79e168afd74e41431d | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 2, "slot_index": 0, "slot_role": "new", "source_file": "unpredictable_cluster24.parquet", "source_item_id": "a2ac8f79e168afd74e41431d", "source_rows": 29, "source_task_id": "da3a06bb__Guide_To_What_Fish_Taste_Like__2", "total_occurrences": 3} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0012 | 2,400,072,952 | null | null | 1 | adaptable_train_0012::ep001 | adaptable:19fade5a9ce84b1881002054 | adaptable_table_induction | skill | new | [
{
"prompt": "Learn from examples for a table task. Predict [Position] for the row.\n[Name] Rodrigo Laviņš [Position]\n[Position] =",
"target": "Defenseman",
"candidates": [
"Defenseman",
"Forward",
"Goalie"
],
"source": "UnpredicTable",
"source_id": "2925dc7f_r_Announced___... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Position] for the row.\n[Name] Kristaps Sotnieks [Position]\n[Position] =",
"target": "Defenseman",
"candidates": [
"Defenseman",
"Forward",
"Goalie"
],
"source": "UnpredicTable",
"source_id": "2925dc7f... | [
"Apply the learned table pattern for a table task. Predict [Position] for the row.\n[Name] Māris Bičevskis [Position]\n[Position] =",
"Apply the learned table pattern for a table task. Predict [Position] for the row.\n[Name] Alekandrs Jerofejevs [Position]\n[Position] =",
"Apply the learned table pattern for a ... | 0.5 | 1 | 2 | 1 | null | 19fade5a9ce84b1881002054 | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 1, "slot_role": "new", "source_file": "unpredictable_cluster14.parquet", "source_item_id": "19fade5a9ce84b1881002054", "source_rows": 53, "source_task_id": "2925dc7f_r_Announced___The_Hockey_House__Position", "total_occurrences": 2} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0012 | 2,400,072,952 | null | null | 2 | adaptable_train_0012::ep002 | adaptable:66b2cb5cff0ead3313c2e4cb | adaptable_table_induction | transient | new | [
{
"prompt": "Learn from examples for a table task. Predict [Type] for the row.\n[Title] Magic Town: THE VOGUES [Author] robahull [Total views] 21,555 [Type]\n[Type] =",
"target": "Audio Post",
"candidates": [
"Audio Post",
"Blog entry",
"Page"
],
"source": "UnpredicTable",
... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Dead Man's Stroll: THE REVELS [Author] robahull [Total views] 38,477 [Type]\n[Type] =",
"target": "Audio Post",
"candidates": [
"Audio Post",
"Blog entry",
"Page"
],
"source": "U... | [
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Have Love, Will Travel: THE SONICS [Author] robahull [Total views] 10,725 [Type]\n[Type] =",
"Apply the learned table pattern for a table task. Predict [Type] for the row.\n[Title] Emitt Rhodes: At Last? [Author] wcresser [Tot... | 0 | 0 | 1 | 1 | null | 66b2cb5cff0ead3313c2e4cb | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 0, "slot_index": 2, "slot_role": "new", "source_file": "unpredictable_cluster19.parquet", "source_item_id": "66b2cb5cff0ead3313c2e4cb", "source_rows": 25, "source_task_id": "ab752b26_Popular_content___PopKrazy__Type", "total_occurrences": 1} |
0.2.0 | adaptable | train | UnpredicTable (AdapTable) | adaptable_train_0012 | 2,400,072,952 | null | null | 3 | adaptable_train_0012::ep003 | adaptable:a2ac8f79e168afd74e41431d | adaptable_table_induction | skill | recurrence | [
{
"prompt": "Review examples for a table task. Predict [2] for the row.\n[0] Trout [1] Mild [2]\n[2] =",
"target": "Delicate",
"candidates": [
"Delicate",
"Delicate-Medium",
"Firm",
"Medium",
"Medium-Firm",
"Texture"
],
"source": "UnpredicTable",
"source_i... | [
{
"prompt": "Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Yellowtail [1] Mild [2]\n[2] =",
"target": "Firm",
"candidates": [
"Delicate",
"Delicate-Medium",
"Firm",
"Medium",
"Medium-Firm",
"Texture"
],
"source": "UnpredicTabl... | [
"Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Orange Roughy [1] Mild [2]\n[2] =",
"Apply the learned table pattern for a table task. Predict [2] for the row.\n[0] Alaskan Halibut [1] Mild [2]\n[2] =",
"Apply the learned table pattern for a table task. Predict [2] for the row.\... | 1 | 1 | 3 | 1 | null | a2ac8f79e168afd74e41431d | null | {"configuration": "adaptable", "dataset": "acorn-streams", "dataset_version": "0.2.0", "license": "Apache-2.0", "source": "UnpredicTable (AdapTable)", "split": "train"} | {"n_future_occurrences": 1, "slot_index": 3, "slot_role": "recurrence", "source_file": "unpredictable_cluster24.parquet", "source_item_id": "a2ac8f79e168afd74e41431d", "source_rows": 29, "source_task_id": "da3a06bb__Guide_To_What_Fish_Taste_Like__2", "total_occurrences": 3} |
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