Triple

T5873754
Position Surface form Disambiguated ID Type / Status
Subject Corunna E130578 entity
Predicate hasAlternativeName P39 FINISHED
Object A Coruña E198582 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: A Coruña | Statement: [Corunna, hasAlternativeName, A Coruña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A Coruña
Context triple: [Corunna, hasAlternativeName, A Coruña]
  • A. A Coruña chosen
    A Coruña is a coastal city in northwestern Spain known for its historic lighthouse, the Tower of Hercules, and its role as an important cultural and economic center in the region.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • C. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • D. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • E. Vigo
    Vigo is a major industrial and port city in northwestern Spain, known for its shipbuilding, fishing industry, and location on the Atlantic coast of Galicia.
  • 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035fafb54819085378e7c8d137402 completed March 22, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b11b48d88190ba6cd5ade2f47a89 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:57 p.m.