Triple
T8788430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Nouvelle-Aquitaine |
E209099
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Angoulême |
E235549
|
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: Angoulême | Statement: [TER Nouvelle-Aquitaine, servesCity, Angoulême]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angoulême Context triple: [TER Nouvelle-Aquitaine, servesCity, Angoulême]
-
A.
Angoulême
chosen
Angoulême is a historic city in southwestern France known for its hilltop old town, medieval ramparts, and status as a major center of the French comics industry.
-
B.
Saintes
Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
-
C.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
D.
Blois
Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
-
E.
Saumur
Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f89a84c819085d4cfe4e6dfbda8 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d04729c39c8190a88a28288653399b |
completed | April 3, 2026, 11:03 p.m. |
Created at: March 30, 2026, 6:43 p.m.