Triple

T21862359
Position Surface form Disambiguated ID Type / Status
Subject Chester Gould E539795 entity
Predicate givenName P17 FINISHED
Object Chester 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: Chester | Statement: [Chester Gould, givenName, Chester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chester
Context triple: [Chester Gould, givenName, Chester]
  • A. Chester chosen
    Chester is the given name of Chester W. Nimitz, the prominent U.S. Navy fleet admiral who played a leading role in the Pacific theater during World War II.
  • B. Chester
    Chester is a historic walled city in northwest England known for its Roman heritage, medieval architecture, and distinctive two-tiered shopping galleries called the Rows.
  • C. Chester
    Chester is a historic walled city in northwest England renowned for its Roman heritage, medieval architecture, and well-preserved city walls.
  • D. Chester
    Chester is a historic walled city in northwest England, renowned for its well-preserved Roman and medieval architecture.
  • E. Chester
    Chester is a historic city in northwest England known for its Roman walls, medieval architecture, and distinctive black-and-white timbered buildings.
  • 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_69e0c47829648190bbe2d1d7033768ec completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0d63beb00819092b8ec3a8ef55a39 completed April 28, 2026, 3:46 p.m.
Created at: April 16, 2026, 6:56 p.m.