Triple

T10234384
Position Surface form Disambiguated ID Type / Status
Subject Edgar Tanner E243423 entity
Predicate workLocation P7 FINISHED
Object Victoria E20514 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: [Edgar Tanner, workLocation, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Edgar Tanner, 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 chosen
    Victoria is a southeastern Australian state known for its capital city Melbourne, cultural diversity, and varied landscapes ranging from coastal regions to alpine areas.
  • D. Victoria
    Victoria was the Spanish carrack that became the first ship to successfully circumnavigate the globe during Ferdinand Magellan’s expedition.
  • E. Victoria
    Victoria is a feminine given name of Latin origin meaning "victory," borne by numerous notable figures including queens, saints, and public personalities.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d20cd8708190ba42752597d62008 completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f74c66048190a0ba1cba593cccb5 completed April 9, 2026, 12:48 a.m.
Created at: April 6, 2026, 11:21 a.m.