Triple

T13201039
Position Surface form Disambiguated ID Type / Status
Subject Province of Madrid E314239 entity
Predicate contains P35 FINISHED
Object Navalcarnero E80242 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: Navalcarnero | Statement: [Province of Madrid, contains, Navalcarnero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Navalcarnero
Context triple: [Province of Madrid, contains, Navalcarnero]
  • A. Navalcarnero chosen
    Navalcarnero is a historic town and municipality in central Spain known for its traditional architecture, wine production, and location southwest of Madrid.
  • B. Escuaín
    Escuaín is a small village in the Spanish Pyrenees, known as a gateway to the scenic Escuaín Gorge within Ordesa y Monte Perdido National Park.
  • C. Marín
    Marín is a coastal town in the province of Pontevedra, Galicia, Spain, known for its naval traditions and as a base of the Spanish Navy.
  • D. Mola
    Mola is a Spanish surname most notably associated with Emilio Mola, a key Nationalist general during the Spanish Civil War.
  • E. Mola
    Mola is a genus of large ocean sunfishes known for their distinctive flattened bodies and immense size, including the common ocean sunfish Mola mola.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c6591d881909a6ebc22246caead completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f60ae01c8190aa7669d6f574df09 completed May 3, 2026, 7:15 a.m.
Created at: April 9, 2026, 9:16 p.m.