Triple
T8720872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée des Beaux-Arts de Tours |
E207006
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | City of Tours |
E560431
|
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: City of Tours | Statement: [Musée des Beaux-Arts de Tours, operatedBy, City of Tours]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Tours Context triple: [Musée des Beaux-Arts de Tours, operatedBy, City of Tours]
-
A.
city of Tours
chosen
The city of Tours is a historic city in central France, known for its medieval old town, role as a gateway to the Loire Valley châteaux, and rich cultural heritage.
-
B.
City of Vienne
The City of Vienne is a historic commune in southeastern France, renowned for its rich Roman heritage and well-preserved ancient monuments.
-
C.
Laon
Laon is a historic hilltop city in northern France known for its well-preserved medieval architecture and impressive Gothic cathedral.
-
D.
Troyes
Troyes is a historic city in northeastern France, known for its well-preserved medieval old town, half-timbered houses, and Gothic churches.
-
E.
Poitiers
Poitiers is a historic city in western France known for its Romanesque architecture, medieval heritage, and role as a regional center in the Nouvelle-Aquitaine region.
- 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_69cc5d03f0848190a50c77e5cd028ee7 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf516d9d9081909230441dd349dc9e |
completed | April 3, 2026, 5:34 a.m. |
Created at: March 30, 2026, 6:36 p.m.