Triple

T1687020
Position Surface form Disambiguated ID Type / Status
Subject Galicia E36464 entity
Predicate containsProvince P11085 FINISHED
Object Ourense E202011 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: Ourense | Statement: [Galicia, containsProvince, Ourense]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ourense
Context triple: [Galicia, containsProvince, Ourense]
  • A. Ourense chosen
    Ourense is a historic inland city in northwestern Spain known for its thermal springs and Roman bridge over the Miño River.
  • B. A Coruña
    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.
  • C. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • D. 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.
  • E. Astorga
    Astorga is a historic city in the province of León, Spain, known for its Roman heritage, medieval cathedral, and a Modernist Episcopal Palace designed by Antoni Gaudí.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6293c368819094ab0f615e418647 completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb96d12481908f8d7d5c9f1f103f completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:29 p.m.