Triple
T8720010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Bretagne |
E206986
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Auray |
E586177
|
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: Auray | Statement: [TER Bretagne, connectsCity, Auray]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Auray Context triple: [TER Bretagne, connectsCity, Auray]
-
A.
Auray
chosen
Auray is a historic coastal town in Brittany, northwestern France, known for its picturesque old port of Saint-Goustan and medieval architecture.
-
B.
Gouvy
Gouvy is a rural municipality in the Belgian province of Luxembourg, known for its natural landscapes and proximity to the Ardennes region.
-
C.
Hennebont
Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
-
D.
Braye
Braye is a river in central France that serves as a tributary of the Loir.
-
E.
Châteaubriant
Châteaubriant is a historic town in western France known for its medieval castle and role as a local administrative and cultural center.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d02a52c81909f93622ae6920b80 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28f599a481908e93bc5b5c41296e |
completed | April 3, 2026, 2:41 a.m. |
Created at: March 30, 2026, 6:36 p.m.