Triple
T5370058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare de Nantes |
E108824
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Cholet |
E461246
|
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: Cholet | Statement: [Gare de Nantes, connectsTo, Cholet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cholet Context triple: [Gare de Nantes, connectsTo, Cholet]
-
A.
Cholet
chosen
Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
-
B.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
-
C.
Langres
Langres is a historic fortified town in northeastern France known for its well-preserved ramparts and as the birthplace of Enlightenment philosopher Denis Diderot.
-
D.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
-
E.
Lisieux
Lisieux is a town and commune in the Calvados department of Normandy in northwestern France, known as a major Catholic pilgrimage site associated with Saint Thérèse of Lisieux.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd86873e0c8190bf5ecede2cc2bd8b |
completed | March 20, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfaf2bc1348190a92833a4c4e0e4cd |
completed | March 22, 2026, 8:58 a.m. |
Created at: March 20, 2026, 2:02 p.m.