Triple

T1179420
Position Surface form Disambiguated ID Type / Status
Subject E. Howard Hunt E25101 entity
Predicate familyName P18 FINISHED
Object Hunt E16802 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: Hunt | Statement: [E. Howard Hunt, familyName, Hunt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hunt
Context triple: [E. Howard Hunt, familyName, Hunt]
  • A. Hunt chosen
    Hunt is a common English surname borne by numerous notable figures across fields such as architecture, politics, sports, and the arts.
  • B. The Hunt
    The Hunt is a BBC nature documentary series that explores the dramatic strategies predators and prey use to survive in the wild.
  • C. Chase
    Chase is a major U.S. consumer and commercial banking brand of JPMorgan Chase, offering a wide range of financial services including checking, savings, credit cards, and loans.
  • D. Cheetah Hunt
    Cheetah Hunt is a multi-launch steel roller coaster at Busch Gardens Tampa Bay known for its high speeds, long track layout, and cheetah-inspired theme.
  • E. Hound and Hunter
    Hound and Hunter is an 1892 oil painting by American realist artist Winslow Homer depicting a tense hunting scene in the Florida wilderness.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd1226fc819083d526ecd22af8ef completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f1f1c188190a96f5718c4e7d59d completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:45 p.m.