Triple
T19846641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée Massey |
E476876
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Tarbes city centre |
—
|
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: Tarbes city centre | Statement: [Musée Massey, near, Tarbes city centre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarbes city centre Context triple: [Musée Massey, near, Tarbes city centre]
-
A.
Tarbes
chosen
Tarbes is a historic city in southwestern France, serving as the capital of the Hautes-Pyrénées department at the foot of the Pyrenees.
-
B.
Gare de Tarbes
Gare de Tarbes is the main railway station serving the town of Tarbes in southwestern France, providing regional and long-distance train connections.
-
C.
Bagnères-de-Bigorre
Bagnères-de-Bigorre is a spa and ski resort town in the French Pyrenees, known for its thermal baths and mountain tourism.
-
D.
Montauban
Montauban is a historic city in southern France known for its red-brick architecture and role as the capital of the Tarn-et-Garonne department.
-
E.
Tarbes–Lourdes–Pyrénées Airport
Tarbes–Lourdes–Pyrénées Airport is a regional French airport in the Pyrenees serving the cities of Tarbes and Lourdes, known especially for handling pilgrimage traffic to the nearby Catholic sanctuary at Lourdes.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65809da2c8190bb579ef42513b74d |
completed | April 20, 2026, 4:44 p.m. |
Created at: April 10, 2026, 1:51 p.m.