Triple

T8446658
Position Surface form Disambiguated ID Type / Status
Subject Duncan E199692 entity
Predicate locatedBetween P1262 FINISHED
Object Victoria E332516 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: [Duncan, locatedBetween, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Duncan, locatedBetween, Victoria]
  • A. Victoria chosen
    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
    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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe3152a3c819092efdeab718def7a completed March 31, 2026, 3:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d1ffa988190a7b0a6b1017e144d completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:09 p.m.