Triple

T9071908
Position Surface form Disambiguated ID Type / Status
Subject Fort of Nossa Senhora da Encarnação E217386 entity
Predicate locatedIn P40 FINISHED
Object Carvoeiro E40947 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: Carvoeiro | Statement: [Fort of Nossa Senhora da Encarnação, locatedIn, Carvoeiro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carvoeiro
Context triple: [Fort of Nossa Senhora da Encarnação, locatedIn, Carvoeiro]
  • A. Carvoeiro chosen
    Carvoeiro is a picturesque coastal village in southern Portugal known for its dramatic cliffs, sandy beaches, and role as a popular holiday destination.
  • B. Calheta
    Calheta is a coastal town on the Cape Verdean island of Maio, known for its quiet beaches and traditional island life.
  • C. Espinho
    Espinho is a coastal city and municipality in northern Portugal, known for its beaches, casino, and traditional fishing heritage.
  • D. Odeceixe
    Odeceixe is a coastal village and civil parish in Portugal’s Algarve region, known for its scenic beach at the mouth of the Ribeira de Seixe and its location within the municipality of Aljezur.
  • E. Tavira
    Tavira is a historic coastal town in Portugal’s Algarve region, known for its picturesque old town, Roman bridge, and nearby island beaches.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc955ffa04819086be5763133c5067 completed April 1, 2026, 3:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3e1ac348190aec39a41b8b113dc completed April 5, 2026, 4:24 a.m.
Created at: March 30, 2026, 7:12 p.m.