Triple
T16770388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maladeta Glacier |
E407576
|
entity |
| Predicate | nearLocality |
P350
|
FINISHED |
| Object | Benasque |
E282614
|
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: Benasque | Statement: [Maladeta Glacier, nearLocality, Benasque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benasque Context triple: [Maladeta Glacier, nearLocality, Benasque]
-
A.
Benasque Valley
chosen
Benasque Valley is a scenic glacial valley in the central Pyrenees of Spain, renowned for its high mountain landscapes, hiking and skiing, and proximity to the range’s highest peaks.
-
B.
Arenys de Munt
Arenys de Munt is a municipality in the Maresme comarca of Catalonia, Spain, known for its Mediterranean setting and involvement in early Catalan independence referendums.
-
C.
Peyrins
Peyrins is a small commune in southeastern France’s Drôme department, known for its rural character and proximity to the town of Romans-sur-Isère.
-
D.
Pau-Ferro
Pau-Ferro is a neighborhood in the city of Recife, Brazil.
-
E.
Freixiosa
Freixiosa is a civil parish located in the municipality of Mangualde in central Portugal.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b0361e5081908f58edf766ff3ce0 |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a533e83481909966a7b86c8c8e64 |
completed | May 10, 2026, 3:33 p.m. |
Created at: April 10, 2026, 5:21 a.m.