Triple

T6249536
Position Surface form Disambiguated ID Type / Status
Subject Arima E140010 entity
Predicate hasNeighbouringArea P17964 FINISHED
Object Sangre Grande E554330 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: Sangre Grande | Statement: [Arima, hasNeighbouringArea, Sangre Grande]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sangre Grande
Context triple: [Arima, hasNeighbouringArea, Sangre Grande]
  • A. Sangre Grande chosen
    Sangre Grande is a major town in northeastern Trinidad known as a regional commercial and transportation hub.
  • B. La Barra
    La Barra is a popular seaside resort town in Uruguay known for its beaches, nightlife, and proximity to Punta del Este.
  • C. Mauá
    Mauá is an industrial and residential city located in the metropolitan region of São Paulo, Brazil.
  • D. Rio de Moinhos
    Rio de Moinhos is a civil parish in the municipality of Abrantes in central Portugal, known for its rural character and traditional Portuguese village life.
  • E. Ribeira Grande
    Ribeira Grande is a coastal town and municipality on the island of Santo Antão in Cape Verde, known for its dramatic mountainous landscapes and traditional Cape Verdean culture.
  • 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_69c008b4858c819095b0199114a9a87b completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0633c5f2081909b0246e061f8a7d9 completed March 22, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c2441d4ad88190895237d834f5d9b8 completed March 24, 2026, 7:58 a.m.
Created at: March 22, 2026, 4:24 p.m.