Triple

T10645088
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Area of Barcelona E250814 entity
Predicate containsMunicipality P852 FINISHED
Object Pineda de Mar E879963 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: Pineda de Mar | Statement: [Metropolitan Area of Barcelona, containsMunicipality, Pineda de Mar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pineda de Mar
Context triple: [Metropolitan Area of Barcelona, containsMunicipality, Pineda de Mar]
  • A. Pineda de Mar chosen
    Pineda de Mar is a coastal town and popular tourist destination on the Mediterranean in the province of Barcelona, Catalonia, Spain.
  • B. Jandía
    Jandía is a popular coastal resort area on the southern tip of Fuerteventura in the Canary Islands, known for its long sandy beaches and tourist infrastructure.
  • C. Conil
    Conil is a small village on the island of Lanzarote in Spain’s Canary Islands, forming part of the municipality of Tías.
  • D. Santoña
    Santoña is a coastal town in the autonomous community of Cantabria in northern Spain, historically known for its fishing industry and maritime tradition.
  • E. Pedreña
    Pedreña is a small coastal village in Cantabria, northern Spain, best known as the hometown of legendary golfer Seve Ballesteros.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfe120908190ab91c38d57133739 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69dbb6f0eee08190b4187671356e47ca completed April 12, 2026, 3:14 p.m.
Created at: April 8, 2026, 9:05 p.m.