| --- |
| dataset_info: |
| features: |
| - name: safe_instance_id |
| dtype: string |
| - name: folder_x |
| dtype: string |
| - name: shard_x |
| dtype: string |
| - name: id_x |
| dtype: string |
| - name: source_x |
| dtype: string |
| - name: sampled_text_x |
| dtype: string |
| - name: narrative_label_x |
| dtype: string |
| - name: narrative_confidence_x |
| dtype: float64 |
| - name: topic_classification_x |
| dtype: string |
| - name: topic_confidence_x |
| dtype: float64 |
| - name: is_noise_x |
| dtype: bool |
| - name: full_text_x |
| dtype: string |
| - name: llm_summary_x |
| dtype: string |
| - name: verb_tokens_x |
| dtype: string |
| - name: verb_spans_x |
| dtype: string |
| - name: verb_count_x |
| dtype: float64 |
| - name: event_tokens_x |
| dtype: string |
| - name: event_spans_x |
| dtype: string |
| - name: event_count_x |
| dtype: float64 |
| - name: assigned_span1_x |
| dtype: string |
| - name: assigned_span2_x |
| dtype: string |
| - name: past_tense_verb_rate_x |
| dtype: float64 |
| - name: sentiment_pos_x |
| dtype: float64 |
| - name: sentiment_neg_x |
| dtype: float64 |
| - name: sentiment_neu_x |
| dtype: float64 |
| - name: sentiment_compound_x |
| dtype: float64 |
| - name: pov_first_rate_x |
| dtype: float64 |
| - name: pov_second_rate_x |
| dtype: float64 |
| - name: pov_third_rate_x |
| dtype: float64 |
| - name: pov_dominant_x |
| dtype: string |
| - name: concreteness_mean_x |
| dtype: float64 |
| - name: concreteness_coverage_x |
| dtype: float64 |
| - name: temporal_mention_rate_x |
| dtype: float64 |
| - name: temporal_mention_count_x |
| dtype: float64 |
| - name: agency_focalization_tejo9855 |
| dtype: float64 |
| - name: agency_emotion_tejo9855 |
| dtype: float64 |
| - name: agency_cognition_tejo9855 |
| dtype: float64 |
| - name: agency_change_of_state_tejo9855 |
| dtype: float64 |
| - name: agency_conflict_tejo9855 |
| dtype: float64 |
| - name: agency_focalization_maria |
| dtype: float64 |
| - name: agency_emotion_maria |
| dtype: float64 |
| - name: agency_cognition_maria |
| dtype: float64 |
| - name: agency_change_of_state_maria |
| dtype: float64 |
| - name: agency_conflict_maria |
| dtype: float64 |
| - name: agency_focalization_gold |
| dtype: float64 |
| - name: agency_emotion_gold |
| dtype: float64 |
| - name: agency_cognition_gold |
| dtype: float64 |
| - name: agency_change_of_state_gold |
| dtype: float64 |
| - name: agency_conflict_gold |
| dtype: float64 |
| - name: folder_y |
| dtype: string |
| - name: shard_y |
| dtype: string |
| - name: id_y |
| dtype: string |
| - name: source_y |
| dtype: string |
| - name: sampled_text_y |
| dtype: string |
| - name: narrative_label_y |
| dtype: string |
| - name: narrative_confidence_y |
| dtype: float64 |
| - name: topic_classification_y |
| dtype: string |
| - name: topic_confidence_y |
| dtype: float64 |
| - name: is_noise_y |
| dtype: bool |
| - name: full_text_y |
| dtype: string |
| - name: llm_summary_y |
| dtype: string |
| - name: verb_tokens_y |
| dtype: string |
| - name: verb_spans_y |
| dtype: string |
| - name: verb_count_y |
| dtype: float64 |
| - name: event_tokens_y |
| dtype: string |
| - name: event_spans_y |
| dtype: string |
| - name: event_count_y |
| dtype: float64 |
| - name: assigned_span1_y |
| dtype: string |
| - name: assigned_span2_y |
| dtype: string |
| - name: past_tense_verb_rate_y |
| dtype: float64 |
| - name: sentiment_pos_y |
| dtype: float64 |
| - name: sentiment_neg_y |
| dtype: float64 |
| - name: sentiment_neu_y |
| dtype: float64 |
| - name: sentiment_compound_y |
| dtype: float64 |
| - name: pov_first_rate_y |
| dtype: float64 |
| - name: pov_second_rate_y |
| dtype: float64 |
| - name: pov_third_rate_y |
| dtype: float64 |
| - name: pov_dominant_y |
| dtype: string |
| - name: concreteness_mean_y |
| dtype: float64 |
| - name: concreteness_coverage_y |
| dtype: float64 |
| - name: temporal_mention_rate_y |
| dtype: float64 |
| - name: temporal_mention_count_y |
| dtype: float64 |
| - name: setting_concreteness_mppauk |
| dtype: float64 |
| - name: setting_temporal_grounding_mppauk |
| dtype: float64 |
| - name: setting_spatial_grounding_mppauk |
| dtype: float64 |
| - name: setting_sensory_mppauk |
| dtype: float64 |
| - name: setting_concreteness_tejo9855 |
| dtype: float64 |
| - name: setting_temporal_grounding_tejo9855 |
| dtype: float64 |
| - name: setting_spatial_grounding_tejo9855 |
| dtype: float64 |
| - name: setting_sensory_tejo9855 |
| dtype: float64 |
| - name: setting_concreteness_roda9210 |
| dtype: float64 |
| - name: setting_temporal_grounding_roda9210 |
| dtype: float64 |
| - name: setting_spatial_grounding_roda9210 |
| dtype: float64 |
| - name: setting_sensory_roda9210 |
| dtype: float64 |
| - name: setting_concreteness_gold |
| dtype: float64 |
| - name: setting_temporal_grounding_gold |
| dtype: float64 |
| - name: setting_spatial_grounding_gold |
| dtype: float64 |
| - name: setting_sensory_gold |
| dtype: float64 |
| - name: folder |
| dtype: string |
| - name: shard |
| dtype: string |
| - name: id |
| dtype: string |
| - name: source |
| dtype: string |
| - name: sampled_text |
| dtype: string |
| - name: narrative_label |
| dtype: string |
| - name: narrative_confidence |
| dtype: float64 |
| - name: topic_classification |
| dtype: string |
| - name: topic_confidence |
| dtype: float64 |
| - name: is_noise |
| dtype: bool |
| - name: full_text |
| dtype: string |
| - name: llm_summary |
| dtype: string |
| - name: verb_tokens |
| dtype: string |
| - name: verb_spans |
| dtype: string |
| - name: verb_count |
| dtype: float64 |
| - name: event_tokens |
| dtype: string |
| - name: event_spans |
| dtype: string |
| - name: event_count |
| dtype: float64 |
| - name: assigned_span1 |
| dtype: string |
| - name: assigned_span2 |
| dtype: string |
| - name: past_tense_verb_rate |
| dtype: float64 |
| - name: sentiment_pos |
| dtype: float64 |
| - name: sentiment_neg |
| dtype: float64 |
| - name: sentiment_neu |
| dtype: float64 |
| - name: sentiment_compound |
| dtype: float64 |
| - name: pov_first_rate |
| dtype: float64 |
| - name: pov_second_rate |
| dtype: float64 |
| - name: pov_third_rate |
| dtype: float64 |
| - name: pov_dominant |
| dtype: string |
| - name: concreteness_mean |
| dtype: float64 |
| - name: concreteness_coverage |
| dtype: float64 |
| - name: temporal_mention_rate |
| dtype: float64 |
| - name: temporal_mention_count |
| dtype: float64 |
| - name: span1_is_event_tejo9855 |
| dtype: bool |
| - name: span2_is_event_tejo9855 |
| dtype: bool |
| - name: causality_rating_tejo9855 |
| dtype: string |
| - name: temporal_order_tejo9855 |
| dtype: string |
| - name: span1_is_event_adde1214 |
| dtype: bool |
| - name: span2_is_event_adde1214 |
| dtype: bool |
| - name: causality_rating_adde1214 |
| dtype: string |
| - name: temporal_order_adde1214 |
| dtype: string |
| - name: span1_is_event_gold |
| dtype: bool |
| - name: span2_is_event_gold |
| dtype: bool |
| - name: temporal_order_gold |
| dtype: string |
| - name: causality_rating_gold |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 27231293 |
| num_examples: 456 |
| download_size: 16584563 |
| dataset_size: 27231293 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: odc-by |
| language: |
| - en |
| tags: |
| - manual |
| - narrative |
| size_categories: |
| - n<1K |
| --- |
| |
| # NarraDolma Gold — Human Annotations |
| |
| The human-annotated gold standard behind NarraBert and NarraDolma. It contains |
| **400 passages** sampled from [Dolma](https://huggingface.co/datasets/allenai/dolma) |
| and annotated across all **11 narrative dimensions** plus event relations. This is |
| the validation backbone of the project: every automated label (LLM and NarraBert) |
| is measured against it. |
| |
| - **Paper:** [arXiv:2606.19468](https://arxiv.org/abs/2606.19468) |
| - **Collection:** [Narratives in LLM Pretraining Data](https://huggingface.co/collections/teagrjohnson/narratives-in-llm-pretraining-data) |
| ## What's in the dataset |
| |
| Each row is a 3-sentence passage with its Dolma source and human labels. |
| |
| | Group | Fields | Type | |
| |---|---|---| |
| | Agency | focalization, emotion, cognition, change_of_state, conflict | 1–5 Likert | |
| | Setting | concreteness, temporal_grounding, spatial_grounding, sensory | 1–5 Likert | |
| | Event relations | temporal_order, causal_relation | categorical (per event pair) | |
| |
| - **Temporal order** labels: `span1_first`, `span2_first`, `simultaneous`, `same_event`, `too_hard_to_tell`. |
| - **Causal relation** labels: `direct_cause`, `enables`, `not_related` (collapsed to a binary causal / not-causal label for downstream analysis). |
| - Event-relation labels are annotated at the level of **adjacent event-trigger pairs**, not whole passages, so a passage may contribute multiple event-pair rows. |
| Provenance fields: `dolma_id`, `source`, `topic` (Common Crawl only), and a split |
| indicator (see below). |
| |
| ## Splits |
| |
| For agency and setting, the 400 passages are divided into two **non-overlapping** |
| gold sets of 200: |
| |
| - **Split A** — used to validate the LLM annotators. |
| - **Split B** — held out to evaluate NarraBert. |
| Event-relation annotations were too sparse to split, so event evaluation uses the |
| full annotated set at both stages. |
| |
| ## Annotation & agreement |
| |
| One author annotated all 400 passages across the three tasks. For verification, a |
| second author annotated overlapping subsets (agency *N*=100, setting *N*=30, events |
| *N*=251) and an additional annotator participated in the setting task (*N*=70). |
| |
| Inter-annotator agreement (per-dimension breakdowns in the paper appendix): |
| |
| | Task | Agreement | |
| |---|---| |
| | Agency | mean α = 0.76 (0.69–0.80), MAE 0.62 | |
| | Setting | mean α = 0.70 (0.63–0.75), MAE 0.55 | |
| | Event relations | mean κ = 0.68, mean F1 = 0.91 | |
| |
| Temporal ordering is the hardest dimension (κ = 0.60), in part because of severe |
| class imbalance among temporal relations. |
| |
| ## Intended use & caveats |
| |
| - Designed as a **validation/evaluation set**, not a training set — it is small by |
| design, reflecting the fine-grained, multi-month calibration effort behind it. |
| - Primary annotation used for model validation was conducted by a single author; |
| agreement on some dimensions is modest. |
| ## License & ethical considerations |
| |
| Released under [ODC-By](https://opendatacommons.org/licenses/by/1-0/). Passages are |
| drawn from web-scraped Dolma and may include toxic, explicit, or personal content. |
| Each row carries the Dolma unique ID for rehydration. Please use for research and |
| auditing only. |
| |
| ## Citation |
| |
| ```bibtex |
| @misc{johnson2026narrative, |
| title = {Characterizing Narrative Content in Web-scale LLM Pretraining Data}, |
| author = {Johnson, Teagan and Ash, Elliott and Piper, Andrew and Antoniak, Maria}, |
| year = {2026}, |
| eprint = {2606.19468}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.CL}, |
| url = {https://arxiv.org/abs/2606.19468} |
| } |
| ``` |
