Triple
T14781240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zamudio |
E347392
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Biscay |
E159064
|
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: Biscay | Statement: [Zamudio, locatedIn, Biscay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biscay Context triple: [Zamudio, locatedIn, Biscay]
-
A.
Biscay
chosen
Biscay is a coastal province in northern Spain, known for its capital Bilbao and its role as a historic and cultural center of the Basque Country.
-
B.
Leioa
Leioa is a suburban municipality in the Basque Country in northern Spain, located near Bilbao in the province of Biscay.
-
C.
Abia
Abia is a state in southeastern Nigeria known for its commercial hub Aba and its role in regional trade and industry.
-
D.
Zuberoa
Zuberoa is the Basque-language name for Soule, a small historical and cultural province of the Basque Country located in the French Pyrenees.
-
E.
Garrotxa
Garrotxa is a comarca (county) in northeastern Catalonia, Spain, known for its volcanic landscape, beech forests, and the medieval town of Besalú.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9de3f48190b7706925e2947cf5 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0d00d46c8190b6289a9b8511a8fb |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:31 a.m.