Triple
T4574649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyrénées-Atlantiques |
E123114
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Pau |
E49264
|
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: Pau | Statement: [Pyrénées-Atlantiques, capital, Pau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pau Context triple: [Pyrénées-Atlantiques, capital, Pau]
-
A.
Pau
chosen
Pau is a historic city in southwestern France, known as the capital of the Pyrénées-Atlantiques department and for its scenic location near the Pyrenees mountains.
-
B.
Hendaye
Hendaye is a coastal town in southwestern France on the Atlantic near the Spanish border, known as a gateway to the Basque Country and the Pyrenees.
-
C.
Saint-Jean-Pied-de-Port
Saint-Jean-Pied-de-Port is a historic Basque town in southwestern France, renowned as a gateway to the Pyrenees and a major starting point for the Camino de Santiago pilgrimage.
-
D.
Perpignan
Perpignan is a historic city in southern France near the Spanish border, known for its Catalan culture and Mediterranean climate.
-
E.
Pau-Ferro
Pau-Ferro is a neighborhood in the city of Recife, Brazil.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c9f0bc81908d87f01ab067818a |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde08756548190bb8433854c3efe01 |
completed | March 21, 2026, 12:04 a.m. |
Created at: March 20, 2026, 1:10 p.m.