Triple

T18515068
Position Surface form Disambiguated ID Type / Status
Subject The Changeling E452437 entity
Predicate setting P1957 FINISHED
Object Alicante NE NERFINISHED

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: Alicante | Statement: [The Changeling, setting, Alicante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alicante
Context triple: [The Changeling, setting, Alicante]
  • A. Alicante chosen
    Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
  • B. Alcoy
    Alcoy is an industrial and historically significant city in southeastern Spain, known for its textile heritage, modernist architecture, and famous Moors and Christians festival.
  • C. Valencia
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • D. Valencia
    Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
  • E. Valencia
    Valencia is a city in Ecuador that serves as the capital of Los Ríos Province’s Valencia Canton and is known for its agricultural surroundings and tropical climate.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53349415c8190b989b536e2d1c40a completed April 19, 2026, 7:55 p.m.
Created at: April 10, 2026, 11:36 a.m.