Triple

T17989761
Position Surface form Disambiguated ID Type / Status
Subject Principality of Asturias E430336 entity
Predicate contains P35 FINISHED
Object Avilés E800382 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: Avilés | Statement: [Principality of Asturias, contains, Avilés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avilés
Context triple: [Principality of Asturias, contains, Avilés]
  • A. Avilés chosen
    Avilés is a historic coastal city in northern Spain’s Asturias region, known for its medieval old town and long maritime and industrial heritage.
  • B. Arévalo
    Arévalo is a historic town in Spain’s Castile and León region, known for its well-preserved medieval architecture and Mudejar-style monuments.
  • C. Esquipulas
    Esquipulas is a Guatemalan town and major Catholic pilgrimage center renowned for its venerated Black Christ statue and the Basilica of Esquipulas.
  • D. Villalba
    Villalba is a frazione (hamlet) of the municipality of Guidonia Montecelio in the Lazio region of central Italy.
  • E. Villalba
    Villalba is a small town and comune in central Sicily, Italy, known for its agricultural economy and location within the Province of Caltanissetta.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b29e47a88190be58b79c73d3e652 completed April 19, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a034317b8fc819094ecb73460288316 completed May 12, 2026, 3:11 p.m.
Created at: April 10, 2026, 10:23 a.m.