Triple

T4371411
Position Surface form Disambiguated ID Type / Status
Subject Nathan Ford E98904 entity
Predicate associatedWith P37 FINISHED
Object Parker E44427 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: Parker | Statement: [Nathan Ford, associatedWith, Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parker
Context triple: [Nathan Ford, associatedWith, Parker]
  • A. Parker chosen
    Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
  • B. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • C. Spencer
    Spencer is a 2021 biographical psychological drama film depicting Princess Diana during a tense Christmas holiday with the British royal family, starring Kristen Stewart in the lead role.
  • D. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • E. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • 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_69b3454db3708190aeafd814413c4c3d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3521dffbc8190b9300a7f4f64bdc0 completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e50bcc9481909b0b9d60198dce63 completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:17 p.m.