Triple

T10621253
Position Surface form Disambiguated ID Type / Status
Subject Miguel E250209 entity
Predicate familyName P18 FINISHED
Object Pimentel E611665 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: Pimentel | Statement: [Miguel, familyName, Pimentel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pimentel
Context triple: [Miguel, familyName, Pimentel]
  • A. Pimentel chosen
    Pimentel is a surname of Portuguese and Spanish origin borne by various notable individuals across fields such as science, politics, and the arts.
  • B. Palau Aguilar
    Palau Aguilar is a historic medieval palace in Barcelona’s Gothic Quarter that serves as the main building of the Picasso Museum.
  • C. Mabini
    Mabini is a coastal municipality in the province of Batangas in the Philippines, known for its diving spots and marine biodiversity.
  • D. Vilaflor
    Vilaflor is a high-altitude village on the island of Tenerife in Spain’s Canary Islands, known for its pine forests, traditional architecture, and proximity to Teide National Park.
  • E. Apalit
    Apalit is a municipality in the province of Pampanga in the Philippines, known for its religious festivals and riverside communities along the Pampanga River.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df70b0288190bf6edd705632ff02 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b908e788190bc9e4f327e871a7f completed April 10, 2026, 9:28 p.m.
Created at: April 8, 2026, 8:50 p.m.