Triple

T5873772
Position Surface form Disambiguated ID Type / Status
Subject Corunna E130578 entity
Predicate hasLandmark P105 FINISHED
Object port of 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: port of A Coruña | Statement: [Corunna, hasLandmark, port of A Coruña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: port of A Coruña
Context triple: [Corunna, hasLandmark, port of 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. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • 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. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • E. Port of Castellón
    The Port of Castellón is a commercial and industrial seaport on Spain’s Mediterranean coast that serves as a key maritime gateway for Castellón de la Plana and its surrounding region.
  • 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_69c0e377e1108190b0820f92eab012c2 completed March 23, 2026, 6:53 a.m.
Created at: March 22, 2026, 3:57 p.m.