Triple

T20345117
Position Surface form Disambiguated ID Type / Status
Subject Moers E495845 entity
Predicate hasTwinTown P919 FINISHED
Object La Trinidad 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: La Trinidad | Statement: [Moers, hasTwinTown, La Trinidad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Trinidad
Context triple: [Moers, hasTwinTown, La Trinidad]
  • A. La Trinidad chosen
    La Trinidad is a town located within the Comayagua Department in central Honduras.
  • B. La Trinidad
    La Trinidad is a municipality in the Philippines known as the capital of Benguet province and for its strawberry farms and cool highland climate.
  • C. La Trinidad
    La Trinidad is a Nicaraguan town and municipality known for its agricultural activities and location within the northern highlands.
  • D. Caibarién
    Caibarién is a coastal town and municipality in central Cuba known historically for its fishing industry and nearby keys.
  • E. San Miguelito
    San Miguelito is a municipality located within the Francisco Morazán Department of Honduras.
  • 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67838744481909069b76b25dd4bb9 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:24 a.m.