Triple
T3105910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canal du Midi |
E64828
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Castelnaudary |
E115426
|
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: Castelnaudary | Statement: [Canal du Midi, passesThrough, Castelnaudary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Castelnaudary Context triple: [Canal du Midi, passesThrough, Castelnaudary]
-
A.
Castelnaudary
chosen
Castelnaudary is a historic market town in southern France renowned as a culinary capital for its traditional cassoulet dish.
-
B.
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.
-
C.
Castelroussin
Castelroussin is the French demonym for an inhabitant of the city of Châteauroux in central France.
-
D.
Castelsarrasin
Castelsarrasin is a commune in the Tarn-et-Garonne department in southern France, known as a historic town on the banks of the Garonne River.
-
E.
Draguignan
Draguignan is a town in southeastern France’s Var department, known as a former prefecture and gateway to the Provence region.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29beff08190b6e1eb6b0608d0eb |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20388b7788190b78b9dd2671214ad |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.