Triple

T15307014
Position Surface form Disambiguated ID Type / Status
Subject A414 E365927 entity
Predicate passesThrough P225 FINISHED
Object Hatfield E211873 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: [A414, passesThrough, Hatfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hatfield
Context triple: [A414, passesThrough, Hatfield]
  • A. Hatfield
    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 former coal mining town in South Yorkshire, England, historically associated with the Yorkshire coalfield.
  • C. Hatfield chosen
    Hatfield is a historic town in Hertfordshire, England, known for Hatfield House and its strong connections to Tudor and Stuart royal history.
  • D. Carlisle
    Carlisle is a fictional vampire doctor and patriarch of the Cullen family in Stephenie Meyer's Twilight series.
  • E. 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.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd001b48190bbdd69337efdb907 completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef89feda88190b18f6a03d6e968aa completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.