Triple
T14626040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montereau-Fault-Yonne |
E343349
|
entity |
| Predicate | locatedInCanton |
P3942
|
FINISHED |
| Object | Montereau-Fault-Yonne |
—
|
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: Montereau-Fault-Yonne | Statement: [Montereau-Fault-Yonne, locatedInCanton, Montereau-Fault-Yonne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montereau-Fault-Yonne Context triple: [Montereau-Fault-Yonne, locatedInCanton, Montereau-Fault-Yonne]
-
A.
Montereau-Fault-Yonne
chosen
Montereau-Fault-Yonne is a commune in north-central France where the Yonne River meets the Seine, historically noted as a strategic river junction and site of significant battles.
-
B.
Morsang-sur-Seine
Morsang-sur-Seine is a small commune in the Essonne department in northern France, situated along the Seine River and within the southern suburbs of Paris.
-
C.
Essonnes
Essonnes was a former commune in northern France that later became part of the town of Corbeil-Essonnes in the Île-de-France region.
-
D.
Crosne
Crosne is a small suburban commune in the Île-de-France region of northern France, located southeast of Paris.
-
E.
Grigny
Grigny is a suburban commune in the southern outskirts of Paris, France, known for its large housing estates and diverse population.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb46a4a9081908472b0a542028a7f |
completed | April 14, 2026, 9:40 p.m. |
Created at: April 10, 2026, 1:26 a.m.