Triple
T4874896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Leu-la-Forêt |
E109175
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Taverny |
E258288
|
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: Taverny | Statement: [Saint-Leu-la-Forêt, locatedNear, Taverny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taverny Context triple: [Saint-Leu-la-Forêt, locatedNear, Taverny]
-
A.
Taverny
chosen
Taverny is a suburban commune in the northwestern outskirts of Paris, located in the Val-d'Oise department in northern France.
-
B.
Pontavenais
Pontavenais is the French demonym for inhabitants of the town of Pont-Aven in Brittany.
-
C.
Benacre
Benacre is a small coastal village and civil parish in the county of Suffolk in eastern England, known for its rural landscape and proximity to the Benacre National Nature Reserve.
-
D.
Larroquette
Larroquette is the surname of John Larroquette, an American actor best known for his Emmy-winning role as Dan Fielding on the sitcom "Night Court."
-
E.
Remigny
Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6da1b45881909d45cb1214f5bdde |
completed | March 20, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67f90e848190a36eee1e670657e4 |
completed | March 21, 2026, 9:42 a.m. |
Created at: March 20, 2026, 1:27 p.m.