Triple

T19481091
Position Surface form Disambiguated ID Type / Status
Subject Tommy Smith E487383 entity
Predicate playedProfessionallyInCountry P10863 FINISHED
Object United States NE NERFINISHED

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: United States | Statement: [Tommy Smith, playedProfessionallyInCountry, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: United States
Context triple: [Tommy Smith, playedProfessionallyInCountry, United States]
  • A. United States of America chosen
    The United States of America is a large federal republic in North America known for its global political, economic, military, and cultural influence.
  • B. Usa
    Usa is a city in Ōita Prefecture, Japan, known for the historic Usa Jingū Shinto shrine.
  • C. Amreeka
    Amreeka is a 2009 independent drama film that follows a Palestinian single mother and her son as they navigate the challenges of immigrant life in small-town America.
  • D. USA
    USA is a public research university located in Mobile, Alabama, known for its diverse academic programs and regional impact in the Gulf Coast area.
  • E. USA
    USA is the three-letter International Olympic Committee country code representing the United States of America in international sporting events.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e634393b8081909f5e4c38b2f1a9b7 completed April 20, 2026, 2:12 p.m.
Created at: April 10, 2026, 1:39 p.m.