Triple
T8531284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deuil-la-Barre |
E201955
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Montmorency |
E214248
|
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: Montmorency | Statement: [Deuil-la-Barre, near, Montmorency]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montmorency Context triple: [Deuil-la-Barre, near, Montmorency]
-
A.
Montmorency
chosen
Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
-
B.
Montmorency
Montmorency is a Montreal Metro station in Laval that serves as the eastern terminus of the Orange Line and a key transit hub for the area.
-
C.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
D.
Vallières
Vallières is a commune in the Nord-Est department of Haiti, known as a small rural settlement within the country’s northern region.
-
E.
Butte-aux-Cailles
Butte-aux-Cailles is a picturesque, village-like neighborhood in Paris known for its cobbled streets, street art, and lively cafés.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe67546248190b359c845c0161ad3 |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce890333d08190b510d970e6d6fee5 |
completed | April 2, 2026, 3:19 p.m. |
Created at: March 30, 2026, 6:17 p.m.