Triple
T16771873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blainville-sur-Orne |
E407616
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Colombelles |
E645332
|
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: Colombelles | Statement: [Blainville-sur-Orne, locatedNear, Colombelles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colombelles Context triple: [Blainville-sur-Orne, locatedNear, Colombelles]
-
A.
Colombelles
chosen
Colombelles is a commune in the Calvados department of the Normandy region in northwestern France, situated near the city of Caen.
-
B.
Cornillon
Cornillon is a commune-level town located in Haiti’s Ouest Department.
-
C.
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."
-
D.
Labarde
Labarde is a commune in southwestern France’s Bordeaux wine region, known for producing prestigious Margaux appellation wines.
-
E.
Les Breuleux
Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b036ff788190bd9f166c3f127818 |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b28592c08190855a7fa5b0a350f5 |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:21 a.m.