Triple
T11791675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commune of Bondy |
E280401
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Noisy-le-Sec |
E690037
|
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: Noisy-le-Sec | Statement: [Commune of Bondy, locatedNear, Noisy-le-Sec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noisy-le-Sec Context triple: [Commune of Bondy, locatedNear, Noisy-le-Sec]
-
A.
Noisy-le-Sec
chosen
Noisy-le-Sec is a suburban commune in the northeastern outskirts of Paris, France, known for its residential character and integration into the Greater Paris metropolitan area.
-
B.
Noisy-le-Grand
Noisy-le-Grand is a suburban commune in the eastern outskirts of Paris, France, known for its modern architecture and role as a business and educational hub within the Marne-la-Vallée area.
-
C.
Le Vésinet
Le Vésinet is a suburban town in the western outskirts of Paris, France, known for its landscaped parks, lakes, and villa-style residential character.
-
D.
Loison
Loison is a small river in northeastern France that serves as a tributary of the Chiers.
-
E.
Vaucresson
Vaucresson is a suburban commune in the western outskirts of Paris, France, known for its residential character and green surroundings.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a588d2c881909783c2d678c2a474 |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00679214208190a9ee4cce882f59cb |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.