Triple

T8398347
Position Surface form Disambiguated ID Type / Status
Subject Sir Andrew Clarke E198108 entity
Predicate workLocation P7 FINISHED
Object Victoria E224124 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: [Sir Andrew Clarke, workLocation, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Sir Andrew Clarke, workLocation, 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 vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • C. Victoria
    Victoria is a feminine given name of Latin origin meaning "victory," borne by numerous notable figures including queens, saints, and public personalities.
  • D. Victoria chosen
    Victoria is a major city in southeastern Australia and the capital of the state of Victoria, known for its rich cultural scene, historic architecture, and status as a key economic and population center.
  • E. Victoria
    Victoria is a Canadian national honour recognizing outstanding achievement and service, associated with the motto of the Order of Canada (CVO).
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb818a8dc081908efd5d7f910322e7 completed March 31, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde85ee7b08190bfbcbed0edb142dd completed April 2, 2026, 3:54 a.m.
Created at: March 30, 2026, 6:04 p.m.