Triple

T15161199
Position Surface form Disambiguated ID Type / Status
Subject Government of Navarre E362219 entity
Predicate hasSeatIn P3522 FINISHED
Object Pamplona E151451 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: Pamplona | Statement: [Government of Navarre, hasSeatIn, Pamplona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pamplona
Context triple: [Government of Navarre, hasSeatIn, Pamplona]
  • A. Pamplona chosen
    Pamplona is a historic city in northern Spain, best known internationally for its annual Running of the Bulls during the San Fermín festival.
  • B. Pamplona
    Pamplona is a historic Colombian city in the Andean region known for its colonial architecture, religious heritage, and role as an educational and cultural center.
  • C. Pamplona
    Pamplona is a landlocked agricultural municipality in the province of Negros Oriental in the Philippines, known for its hilly terrain and rural communities.
  • D. Bilbao
    Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
  • E. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060f2efc8190aa0eb5fb8d4ce085 completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef64dbfc819098dac50500673ed4 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:08 a.m.