Triple

T13667817
Position Surface form Disambiguated ID Type / Status
Subject Humphrey Goodman E327667 entity
Predicate givenName P17 FINISHED
Object Humphrey E246706 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: Humphrey | Statement: [Humphrey Goodman, givenName, Humphrey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Humphrey
Context triple: [Humphrey Goodman, givenName, Humphrey]
  • A. Humphrey chosen
    Humphrey is a masculine given name of Old German origin, traditionally associated with nobility and strength.
  • B. Ralph Willard
    Ralph Willard is an American college basketball coach best known for successful head coaching stints at programs such as Western Kentucky, Pittsburgh, and Holy Cross.
  • C. Alan Johnson
    Alan Johnson is a British Labour politician who served as Home Secretary and held several other senior cabinet positions under Prime Ministers Tony Blair and Gordon Brown.
  • D. Joseph Swing
    Joseph Swing was a U.S. Army general and later Commissioner of the Immigration and Naturalization Service, best known for directing large-scale immigration enforcement efforts in the 1950s.
  • E. Charles Alexander Gore
    Charles Alexander Gore was a 19th-century British public official who held senior administrative roles in the management of Crown lands and forests.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65832688190aea688fee0a7cbdb completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b0cfe0c8190b0fe50931e9788cf completed May 3, 2026, 5:51 p.m.
Created at: April 9, 2026, 9:52 p.m.