Triple

T7554552
Position Surface form Disambiguated ID Type / Status
Subject Harold Shand E178625 entity
Predicate hasPartner P1136 FINISHED
Object Victoria E346112 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: Victoria | Statement: [Harold Shand, hasPartner, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Harold Shand, hasPartner, Victoria]
  • A. Victoria
    Victoria is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and agricultural economy.
  • B. Victoria
    Victoria is a coastal city on the southern tip of Vancouver Island known for its historic architecture, mild climate, and vibrant tourism industry.
  • C. Victoria chosen
    Victoria is a vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • D. Victoria
    Victoria is a British historical drama television series that chronicles the early life and reign of Queen Victoria.
  • E. Victoria
    Victoria was a German princess of Saxe-Coburg-Saalfeld best known as the mother of Queen Victoria of the United Kingdom.
  • 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_69c69f2da22c8190a50942ac20af70e8 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8b990148190b26a3a262cf538b3 completed March 27, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86836bf588190aa1b4104c2d06a1f completed March 28, 2026, 11:45 p.m.
Created at: March 27, 2026, 3:49 p.m.