Triple

T6693410
Position Surface form Disambiguated ID Type / Status
Subject Mark O. Hatfield E152685 entity
Predicate familyName P18 FINISHED
Object Hatfield E152685 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: Hatfield | Statement: [Mark O. Hatfield, familyName, Hatfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hatfield
Context triple: [Mark O. Hatfield, familyName, Hatfield]
  • A. Hatfield chosen
    Hatfield is a surname most prominently associated with Mark O. Hatfield, a long-serving U.S. senator and governor from Oregon.
  • B. Hatfield
    Hatfield is a historic town in Hertfordshire, England, known for Hatfield House and its strong connections to Tudor and Stuart royal history.
  • C. Carlisle
    Carlisle is a historic cathedral city and county town of Cumbria in North West England, near the Scottish border.
  • D. Carlisle
    Carlisle is a historic borough in south-central Pennsylvania known for its military education institutions, colonial heritage, and role in the American Revolutionary era.
  • E. Winster
    Winster is a historic village in England’s Peak District, known for its traditional stone houses, former lead-mining heritage, and well-preserved conservation area.
  • 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b1955e448190adbfed7dc28f8c52 completed March 27, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b97210819086e88624c476fa24 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:05 p.m.