Triple

T7262259
Position Surface form Disambiguated ID Type / Status
Subject Ellen Louise Axson Wilson E159683 entity
Predicate familyName P18 FINISHED
Object Wilson E4321 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wilson | Statement: [Ellen Louise Axson Wilson, familyName, Wilson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilson
Context triple: [Ellen Louise Axson Wilson, familyName, Wilson]
  • A. Wilson chosen
    Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
  • B. Wilson
    "Wilson" is a 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
  • C. Wilson
    Wilson is a small city in eastern North Carolina known historically for its tobacco and textile industries and now for its diversified economy and educational institutions.
  • D. Wilson
    Wilson is a city in eastern North Carolina known historically for its tobacco and textile industries and now for its cultural attractions and public gardens.
  • E. Wilson
    Wilson is a well-known American sporting goods manufacturer recognized especially for its basketballs and other professional sports equipment.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac8bc908190b0e4da5474ecb62f completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3c3bfb48190877ba03ab0851a68 completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:57 p.m.