Triple

T13510508
Position Surface form Disambiguated ID Type / Status
Subject Arnulf de Montgomery E321126 entity
Predicate residence P75 FINISHED
Object Pembroke E89541 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: Pembroke | Statement: [Arnulf de Montgomery, residence, Pembroke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pembroke
Context triple: [Arnulf de Montgomery, residence, Pembroke]
  • A. Pembroke chosen
    Pembroke is a historic town in southwest Wales best known as the birthplace of King Henry VII of England and for its prominent medieval castle.
  • B. Pembroke
    Pembroke is a suburban town in southeastern Massachusetts known for its residential character, ponds, and historic New England charm.
  • C. Pembroke
    Pembroke is a small Canadian city in eastern Ontario known for its location along the Ottawa River and its role as a regional service and cultural center.
  • D. Pembroke
    Pembroke is a given name most notably borne by American film editor Pembroke J. Herring, known for his work on numerous major Hollywood productions.
  • E. Pembroke
    Pembroke is a small city in southeastern Georgia that serves as the administrative and governmental center of Bryan County.
  • 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.