Triple

T22970340
Position Surface form Disambiguated ID Type / Status
Subject Taylor E571169 entity
Predicate isCommonIn P1393 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: [Taylor, isCommonIn, United States]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: United States
Context triple: [Taylor, isCommonIn, 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_69e245b2c6548190a0e4c7f2f7df2d48 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1823272c4819083e4653d231facec completed April 29, 2026, 3:59 a.m.
Created at: April 17, 2026, 3:48 p.m.