Triple

T8206778
Position Surface form Disambiguated ID Type / Status
Subject Lugo E191706 entity
Predicate hasNeighbouringProvince P62207 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: [Lugo, hasNeighbouringProvince, Ourense]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ourense
Context triple: [Lugo, hasNeighbouringProvince, 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. Mondoñedo
    Mondoñedo is a historic town in northwestern Spain, renowned for its medieval cathedral and former status as an important ecclesiastical and administrative center in the region of Galicia.
  • C. 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.
  • D. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • E. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb726b520081908ce4a03bd14dfcdf completed March 31, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34b49fb88190b30a89d594ed4ada completed April 1, 2026, 3:07 p.m.
Created at: March 30, 2026, 5:43 p.m.