Triple
T17625864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A10 motorway |
E429840
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Blois |
—
|
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: Blois | Statement: [A10 motorway, servesCity, Blois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blois Context triple: [A10 motorway, servesCity, Blois]
-
A.
Blois
chosen
Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
-
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.
Melun
Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
-
D.
Pithiviers
Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
-
E.
La Châtre
La Châtre is a small historic town in central France known for its picturesque medieval streets and its association with the writer George Sand.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dbc62e88190b9757dc7c52d7fee |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 5:52 a.m.