Triple

T1003879
Position Surface form Disambiguated ID Type / Status
Subject Armstrong County E21664 entity
Predicate hasSettlement P1068 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: [Armstrong County, hasSettlement, Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parker
Context triple: [Armstrong County, hasSettlement, 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 masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • D. Spencer
    Spencer is the middle name of American author and aviator Anne Spencer Lindbergh, reflecting her family’s naming tradition.
  • E. Elliott
    Elliott is a masculine given name of English origin, often used as both a first name and a surname.
  • 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_69a493c53e648190ae8cb76c433fd9a7 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4ff614081909478500ada1f5059 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a1ecddc8190b954d16c6e269498 completed March 7, 2026, 1:37 p.m.
Created at: March 1, 2026, 7:41 p.m.