Triple
T22824519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alquézar |
E565315
|
entity |
| Predicate | accessFrom |
P1985
|
FINISHED |
| Object | Barbastro |
—
|
NE NERFINISHED |
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: Barbastro | Statement: [Alquézar, accessFrom, Barbastro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbastro Context triple: [Alquézar, accessFrom, Barbastro]
-
A.
Barbastro
chosen
Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
-
B.
Albarracín
Albarracín is a historic hilltop town in eastern Spain renowned for its well-preserved medieval architecture and dramatic red sandstone setting.
-
C.
Daroca
Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
-
D.
Burriana
Burriana is a coastal town in Spain’s Valencian Community known for its Mediterranean beaches and role as a holiday resort on the Costa del Azahar.
-
E.
Calatayud
Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dd34a248190881f2bccdd9aedce |
completed | April 29, 2026, 3:41 a.m. |
Created at: April 17, 2026, 3:34 p.m.