Triple
T17592175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare de Caen |
E428473
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Rennes |
—
|
NE NERFINISHED |
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: Rennes | Statement: [Gare de Caen, connectsTo, Rennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rennes Context triple: [Gare de Caen, connectsTo, Rennes]
-
A.
Rennes
chosen
Rennes is the capital city of France’s Brittany region, known for its historic medieval center, vibrant student population, and role as a major cultural and economic hub in western France.
-
B.
Nantes
Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
-
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.
Rouen
Rouen is a historic city in northern France renowned for its medieval architecture, Gothic cathedral, and association with figures like Joan of Arc and the Impressionist painter Claude Monet.
-
E.
La Rochelle
La Rochelle is a historic French Atlantic port city that became a major stronghold and refuge for Huguenots during the French Wars of Religion.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e79dac8190953a1ce8fc015b20 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 5:51 a.m.