Triple

T14606507
Position Surface form Disambiguated ID Type / Status
Subject Province of Pontevedra E342842 entity
Predicate contains P35 FINISHED
Object Baiona E693368 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: Baiona | Statement: [Province of Pontevedra, contains, Baiona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baiona
Context triple: [Province of Pontevedra, contains, Baiona]
  • A. Baiona chosen
    Baiona is a coastal town in the province of Pontevedra in Galicia, northwestern Spain, known for its historic harbor and medieval old quarter.
  • B. Mahón
    Mahón is the principal city and administrative center of the Spanish Balearic island of Menorca, known for its large natural harbor and historic architecture.
  • C. Sa Dec
    Sa Dec is a riverside city in Vietnam’s Mekong Delta, known for its ornamental flower villages, traditional markets, and French colonial-era architecture.
  • D. Blanes
    Blanes is a coastal town in Catalonia, Spain, known as the southern gateway to the Costa Brava and popular for its beaches, botanical gardens, and summer tourism.
  • E. Balmaseda
    Balmaseda is a historic town in northern Spain’s Basque Country, known as the first officially chartered town in the province of Biscay and noted for its medieval bridge and old quarter.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44d327c8190a8d20568429d0f80 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d09e988190a2a2a1332397b412 completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.