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description
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10 values
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bool
1 class
query_prompt
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10 values
query
stringclasses
10 values
entity_a
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entity_b
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10 values
rel_b
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9 values
prompt
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raw_responses
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10 values
[ "Q96581197", "P57", "Q100719246" ]
[ "Q96581188", "P57", "Q100719246" ]
[ "Q100719246", "P1327", "Q96581197" ]
[ "Jerémy Trouilh", "director", "Gagarine" ]
[ "Fanny Liatard", "director", "Gagarine" ]
[ "Gagarine", "partner in business or sport", "Jerémy Trouilh" ]
Q100719246__P57
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting Jerémy Trouilh, a notable figure, and someone who has been a partner in business or sport with him?
Jerémy Trouilh
Jerémy Trouilh
partner in business or sport
Query: What are different ways of connecting Jerémy Trouilh, a notable figure, and someone who has been a partner in business or sport with him? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) for...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"Jer\u00e9my Trouilh\",\n \"collaborated with\",\n \"Fanny Liatard\"\n ],\n [\n \"Fanny Liatard\",\n \"partner in business or sport\",\n \"Jer\u00e9my Trouilh\"\n ]\n ],\n \"2\": [\n [\n \"Jer\u...
[ "Q18048619", "P2293", "Q131755" ]
[ "Q18045544", "P2293", "Q131755" ]
[ "Q18045544", "P5572", "Q107244" ]
[ "TMEM132C", "genetic association", "bipolar disorder" ]
[ "CDH23", "genetic association", "bipolar disorder" ]
[ "CDH23", "expressed in", "monocyte" ]
Q131755__P2293
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting TMEM132C, a gene associated with certain biological functions, and a substance that is expressed in monocytes?
TMEM132C
monocyte
expressed in
Query: What are different ways of connecting TMEM132C, a gene associated with certain biological functions, and a substance that is expressed in monocytes? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"TMEM132C\",\n \"associated with\",\n \"hearing loss\"\n ],\n [\n \"hearing loss\",\n \"associated with\",\n \"GJB2\"\n ],\n [\n \"GJB2\",\n \"expressed in\",\n \"monocyte\"\n ]\n ],...
[ "Q422606", "P2175", "Q12199" ]
[ "Q304330", "P2175", "Q12199" ]
[ "Q304330", "P527", "Q623" ]
[ "didanosine", "medical condition treated", "HIV/AIDS" ]
[ "abacavir", "medical condition treated", "HIV/AIDS" ]
[ "abacavir", "has part(s)", "carbon" ]
Q12199__P2175
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting didanosine, a medication used to treat HIV, and a substance that has carbon as one of its components?
didanosine
carbon
has part(s)
Query: What are different ways of connecting didanosine, a medication used to treat HIV, and a substance that has carbon as one of its components? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) f...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"didanosine\",\n \"chemical formula\",\n \"C10H12N4O3\"\n ],\n [\n \"C10H12N4O3\",\n \"has part(s)\",\n \"carbon\"\n ]\n ],\n \"2\": [\n [\n \"didanosine\",\n \"is a\",\n \"nucleoside ...
[ "Q1702841", "P54", "Q219714" ]
[ "Q19865964", "P54", "Q219714" ]
[ "Q19865964", "P413", "Q528145" ]
[ "Jon Runyan", "member of sports team", "Philadelphia Eagles" ]
[ "Ephesians Bartley", "member of sports team", "Philadelphia Eagles" ]
[ "Ephesians Bartley", "position played on team / speciality", "linebacker" ]
Q219714__P54
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting Jon Runyan, the former American football player, and someone who played as a linebacker on a football team?
Jon Runyan
linebacker
position played on team / speciality
Query: What are different ways of connecting Jon Runyan, the former American football player, and someone who played as a linebacker on a football team? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, t...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"Jon Runyan\",\n \"child\",\n \"Jon Runyan Jr.\"\n ],\n [\n \"Jon Runyan Jr.\",\n \"teammate\",\n \"Rashan Gary\"\n ],\n [\n \"Rashan Gary\",\n \"position played on team / speciality\",\n ...
[ "Q313875", "P463", "Q254138" ]
[ "Q18218142", "P463", "Q254138" ]
[ "Q18218142", "P1303", "Q6607" ]
[ "Shawn Crahan", "member of", "Slipknot" ]
[ "Alessandro Venturella", "member of", "Slipknot" ]
[ "Alessandro Venturella", "instrument", "guitar" ]
Q254138__P463
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting Shawn Crahan, the musician known for his work with Slipknot, and someone who plays the guitar?
Shawn Crahan
guitar
instrument
Query: What are different ways of connecting Shawn Crahan, the musician known for his work with Slipknot, and someone who plays the guitar? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) forming ...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"Shawn Crahan\",\n \"member of\",\n \"Slipknot\"\n ],\n [\n \"Slipknot\",\n \"has member\",\n \"Mick Thomson\"\n ],\n [\n \"Mick Thomson\",\n \"instrument\",\n \"guitar\"\n ]\n ],\n ...
[ "Q10328595", "P58", "Q2848040" ]
[ "Q10328595", "P58", "Q1704125" ]
[ "Q1704125", "P106", "Q36180" ]
[ "Memórias Póstumas", "screenwriter", "André Klotzel" ]
[ "Memórias Póstumas", "screenwriter", "José Roberto Torero" ]
[ "José Roberto Torero", "occupation", "writer" ]
Q10328595__P58
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting André Klotzel, a Brazilian filmmaker, and someone who is a writer by profession?
André Klotzel
writer
occupation
Query: What are different ways of connecting André Klotzel, a Brazilian filmmaker, and someone who is a writer by profession? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) forming a continuous c...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\"Andr\u00e9 Klotzel\", \"directed\", \"A Marvada Carne\"],\n [\"A Marvada Carne\", \"screenwriter\", \"Andr\u00e9 Klotzel\"],\n [\"Andr\u00e9 Klotzel\", \"occupation\", \"writer\"]\n ],\n \"2\": [\n [\"Andr\u00e9 Klotzel\", \"directed\...
[ "Q1050065", "P58", "Q471000" ]
[ "Q1050065", "P58", "Q577959" ]
[ "Q577959", "P101", "Q115156386" ]
[ "REC 2", "screenwriter", "Jaume Balagueró" ]
[ "REC 2", "screenwriter", "Paco Plaza" ]
[ "Paco Plaza", "field of work", "film screenwriting" ]
Q1050065__P58
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting Jaume Balagueró, the Spanish filmmaker, and someone who works in the field of film screenwriting?
Jaume Balagueró
film screenwriting
field of work
Query: What are different ways of connecting Jaume Balagueró, the Spanish filmmaker, and someone who works in the field of film screenwriting? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) formi...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"Jaume Balaguer\u00f3\",\n \"field of work\",\n \"film screenwriting\"\n ]\n ],\n \"2\": [\n [\n \"Jaume Balaguer\u00f3\",\n \"co-director\",\n \"Paco Plaza\"\n ],\n [\n \"Paco Plaza\",\n \...
[ "Q105081740", "P57", "Q15831456" ]
[ "Q105081740", "P57", "Q3189592" ]
[ "Q3189592", "P69", "Q3578463" ]
[ "The Deep House", "director", "Alexandre Bustillo" ]
[ "The Deep House", "director", "Julien Maury" ]
[ "Julien Maury", "educated at", "École Supérieure de Réalisation Audiovisuelle" ]
Q105081740__P57
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting The Deep House, a horror film, and someone who was educated at the École Supérieure de Réalisation Audiovisuelle?
The Deep House
École Supérieure de Réalisation Audiovisuelle
educated at
Query: What are different ways of connecting The Deep House, a horror film, and someone who was educated at the École Supérieure de Réalisation Audiovisuelle? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relations...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"The Deep House\",\n \"directed by\",\n \"Julien Maury\"\n ],\n [\n \"Julien Maury\",\n \"educated at\",\n \"\u00c9cole Sup\u00e9rieure de R\u00e9alisation Audiovisuelle\"\n ]\n ],\n \"2\": [\n [\n ...
[ "Q66671", "P40", "Q1339" ]
[ "Q309470", "P40", "Q1339" ]
[ "Q309470", "P106", "Q115785313" ]
[ "Maria Elisabeth Lämmerhirt", "child", "Johann Sebastian Bach" ]
[ "Johann Ambrosius Bach", "child", "Johann Sebastian Bach" ]
[ "Johann Ambrosius Bach", "occupation", "court musician" ]
Q1339__P40
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting Maria Elisabeth Lämmerhirt and someone who held the occupation of a court musician?
Maria Elisabeth Lämmerhirt
court musician
occupation
Query: What are different ways of connecting Maria Elisabeth Lämmerhirt and someone who held the occupation of a court musician? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) forming a continuou...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"Maria Elisabeth L\u00e4mmerhirt\",\n \"mother of\",\n \"Johann Sebastian Bach\"\n ],\n [\n \"Johann Sebastian Bach\",\n \"occupation\",\n \"court musician\"\n ]\n ],\n \"2\": [\n [\n \"Maria El...
[ "Q1087499", "P2175", "Q35869" ]
[ "Q417767", "P2175", "Q35869" ]
[ "Q417767", "P3780", "Q47521846" ]
[ "troleandomycin", "medical condition treated", "asthma" ]
[ "montelukast", "medical condition treated", "asthma" ]
[ "montelukast", "active ingredient in", "Singulair" ]
Q35869__P2175
false
Task: Generate a Natural Language Query. You will be given input in the following format: Concept A: entity1 Concept B: entity2 Concept C: (concept B, rel, entity3) Concept A and Concept C are connected via an independent concept B. Concept C is a property of Concept B, which the person is supposed to guess. You...
What are different ways of connecting troleandomycin, a chemical compound, and a substance that is the active ingredient in Singulair?
troleandomycin
Singulair
active ingredient in
Query: What are different ways of connecting troleandomycin, a chemical compound, and a substance that is the active ingredient in Singulair? Task: Identify how two real-world entities are connected by producing MANY connection paths. A connection path is a sequence of factual triples (head, relationship, tail) formin...
{"final_response": "<think>\n\n</think>\n\n<answer>\n{\n \"1\": [\n [\n \"troleandomycin\",\n \"drug class\",\n \"macrolide\"\n ],\n [\n \"macrolide\",\n \"interacts with\",\n \"Cytochrome P450 3A4\"\n ],\n [\n \"Cytochrome P450 3A4\",\n \"metabolizes\",\n \"...

Dataset: connections-dev/connection_queries_jan12

This dataset was generated using the inference script with the following configuration:

Inference Parameters

Model Configuration

  • Model Name: gemini-3-pro-preview
  • Server URL: Not specified
  • API Key: Not provided
  • Request Timeout: 30 seconds

Query Configuration

  • Query Type: natural
  • Query Column: query
  • Sampling Type: original

Generation Parameters

  • Temperature: 0.7
  • Max Tokens: 16384
  • Number of Runs: 1
  • Chunk Size: Entire dataset
  • Effort Level: low

Feature Flags

  • Step by Step Reasoning: False
  • Reasoning Enabled: False
  • No Curator: False
  • Index Filter: None (all samples)
  • Start Index: 70
  • End Index: 80

Data Information

  • Input File: connections-dev/connection_queries_jan12
  • Number of Samples: 10
  • Output Filename: connection_queries_jan12__natural__s70__e80__original__1__low__0.7__16384__gemini-3-pro-preview.jsonl

Dataset Structure

The dataset contains the following key columns:

  • query: The original query
  • entity_a: Starting entity
  • entity_b: Target entity
  • rel_b: Target relationship
  • path_prediction: Generated connection paths
  • prompt_for_path: Prompts used for path generation

Usage

You can load this dataset using:

from datasets import load_dataset

dataset = load_dataset("s70_e80_original_1_low_0.7_16384_gemini-3-pro-preview__raw")

Generation Details

This dataset was generated on 2026-01-22 14:45:48 using the inference pipeline with the above configuration.

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