Triple

T13510492
Position Surface form Disambiguated ID Type / Status
Subject Arnulf de Montgomery E321126 entity
Predicate familyName P18 FINISHED
Object de Montgomery E194744 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: de Montgomery | Statement: [Arnulf de Montgomery, familyName, de Montgomery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: de Montgomery
Context triple: [Arnulf de Montgomery, familyName, de Montgomery]
  • A. de Montgomery chosen
    De Montgomery is a Norman noble family name historically associated with influential medieval lords in England and Normandy.
  • B. Burkley
    Burkley is a surname most notably associated with American character actor Dennis Burkley.
  • C. Huston
    Huston is a surname most famously associated with a prominent American film family that includes acclaimed director John Huston and actress Anjelica Huston.
  • D. Overton
    Overton is a small unincorporated community in southeastern Nevada known as a gateway to the nearby Lake Mead National Recreation Area and the Valley of Fire State Park.
  • E. Monro
    Monro is a variant spelling of the Scottish surname Munro, historically associated with a Highland clan from Easter Ross.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf86a6208190be8c18f7a0158f23 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75490291c8190b5985d8c90ef1af6 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.