Triple
T14556371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rennes railway station |
E341551
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Quimper |
E155143
|
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: Quimper | Statement: [Rennes railway station, connectsTo, Quimper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quimper Context triple: [Rennes railway station, connectsTo, Quimper]
-
A.
Quimper
chosen
Quimper is a historic city in western France known for its medieval old town, Gothic cathedral, and traditional Breton culture.
-
B.
Ploërmel
Ploërmel is a historic town in Brittany, northwestern France, known for its medieval heritage and role as an administrative center in the Morbihan department.
-
C.
Vannes
Vannes is a historic coastal city in northwestern France known for its well-preserved medieval old town and harbor on the Gulf of Morbihan.
-
D.
Quimperlé
Quimperlé is a historic town in the Finistère department of Brittany in northwestern France, known for its medieval architecture and picturesque setting at the confluence of three rivers.
-
E.
Saint-Brieuc
Saint-Brieuc is a coastal city and the capital of the Côtes-d'Armor department in Brittany, northwestern France, known for its historic center and nearby bay.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8abde0308190819da6867e703ea7 |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.