Triple

T7487708
Position Surface form Disambiguated ID Type / Status
Subject Aubagne E176922 entity
Predicate twinnedWith P1072 FINISHED
Object Pontevedra E221545 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: Pontevedra | Statement: [Aubagne, twinnedWith, Pontevedra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pontevedra
Context triple: [Aubagne, twinnedWith, Pontevedra]
  • A. Pontevedra chosen
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • B. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • 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. Ferrol
    Ferrol is a coastal city and major naval shipbuilding center in the Galicia region of northwestern Spain.
  • E. Ourense
    Ourense is a historic inland city in northwestern Spain known for its thermal springs and Roman bridge over the Miño River.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f55965ac81909d3c3a5422b22d44 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8613eaf0c8190b33cb22dd83ee59c completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:43 p.m.