Triple

T7275222
Position Surface form Disambiguated ID Type / Status
Subject Cala d'Or E163008 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Porto Petro E629601 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: Porto Petro | Statement: [Cala d'Or, hasNearbySettlement, Porto Petro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto Petro
Context triple: [Cala d'Or, hasNearbySettlement, Porto Petro]
  • A. Portopetro chosen
    Portopetro is a small coastal village and harbor on the southeast coast of Mallorca, Spain, known for its tranquil bays and traditional Mediterranean character.
  • B. Porto Judeu
    Porto Judeu is a civil parish on Terceira Island in the Azores, Portugal, known for its coastal setting and traditional Azorean character.
  • C. Porto dos Casais
    Porto dos Casais was the original colonial settlement that later developed into the Brazilian city of Porto Alegre.
  • D. Porto da Folha
    Porto da Folha is a municipality in the Brazilian state of Sergipe, located in the semi-arid interior region known for its rural communities and traditional cultural practices.
  • E. Cantanhede
    Cantanhede is a Portuguese municipality in the Centro Region known for its wine production, agricultural activity, and proximity to the Atlantic coast.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb0fd8788190aa21d4b2ad773926 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db2c76fc81909632c7ee4e54f81c completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:58 p.m.