Triple
T19846579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare de Tarbes |
E476875
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Tarbes |
—
|
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 | Statement: [Gare de Tarbes, serves, Tarbes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarbes Context triple: [Gare de Tarbes, serves, Tarbes]
-
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.
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.
-
C.
Narbonne
Narbonne is a historic city in southern France known for its Roman heritage, medieval architecture, and former status as an important Mediterranean port.
-
D.
Eauze
Eauze is a historic town in southwestern France, known as a former Roman capital and a center of Armagnac brandy production.
-
E.
Saint-Girons
Saint-Girons is a small town in the Ariège department of southwestern France, situated in the foothills of the Pyrenees.
- 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.