Triple
T961575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Sanjurjo |
E20746
|
entity |
| Predicate | burialPlace |
P196
|
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: [José Sanjurjo, burialPlace, Pamplona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pamplona Context triple: [José Sanjurjo, burialPlace, 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.
Donostia-San Sebastián
Donostia-San Sebastián is a coastal city in Spain’s Basque Country renowned for its picturesque bay, beaches, and world-class gastronomy.
-
C.
Zaragoza
Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
-
D.
San Sebastián
San Sebastián is a Guatemalan town located in the highlands of the San Marcos department, known for its proximity to Central America’s highest peak, Volcán Tajumulco.
-
E.
Madrid
Madrid is a municipality in the Cundinamarca department of Colombia, located near Bogotá and known for its floriculture and agricultural production.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b415ac688190bbcef455935a3116 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08995af88190930a952bd32cd918 |
completed | March 8, 2026, 5:26 a.m. |
Created at: March 1, 2026, 7:40 p.m.