Triple
T11325142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serris |
E268191
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Montévrain |
E706046
|
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: Montévrain | Statement: [Serris, near, Montévrain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montévrain Context triple: [Serris, near, Montévrain]
-
A.
Montévrain
chosen
Montévrain is a suburban commune in the eastern outskirts of Paris, France, known for its proximity to Disneyland Paris and its role in the Marne-la-Vallée new town development.
-
B.
Franc-Nohain
Franc-Nohain was a French poet, librettist, and lawyer best known for his witty verse and collaborations with composers such as Maurice Ravel.
-
C.
Soissonnais
Soissonnais is a historical region in northern France centered around the city of Soissons, known for its early medieval significance and role in the Frankish kingdom.
-
D.
Ambertois
Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
-
E.
Vendômois
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e122e48190b3f890de8d561480 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e54318be088190b57de40a2091447d |
completed | April 19, 2026, 9:03 p.m. |
Created at: April 8, 2026, 9:32 p.m.