Triple

T16108287
Position Surface form Disambiguated ID Type / Status
Subject Jessica Tate E390798 entity
Predicate hasLoveInterest P7325 FINISHED
Object Chester Tate E1201434 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: Chester Tate | Statement: [Jessica Tate, hasLoveInterest, Chester Tate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chester Tate
Context triple: [Jessica Tate, hasLoveInterest, Chester Tate]
  • A. Chester Tate chosen
    Chester Tate is a fictional character from the satirical TV sitcom "Soap," known as the wealthy, philandering patriarch of the Tate family.
  • B. Fred Tate
    Fred Tate is a child prodigy whose extraordinary intellectual abilities and emotional struggles are central to the drama film "Little Man Tate."
  • C. Chester Conklin
    Chester Conklin was an American silent film comedian and character actor best known for his work with Mack Sennett’s Keystone comedies and later appearances alongside stars like Charlie Chaplin.
  • D. Chester Ashley
    Chester Ashley was a 19th-century American lawyer, land speculator, and U.S. Senator from Arkansas who played a significant role in the early political and legal development of the state.
  • E. Chester Weir
    Chester Weir is a historic low-head weir on the River Dee in Chester, England, built to manage water levels and flow through the city.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e20165aa9c81908c5358cca2b0d0fe completed April 17, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec7cc0881909685923113eaba25 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5 a.m.