Triple
T6492868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thoiry |
E148083
|
entity |
| Predicate | hasBorderingCommune |
P28600
|
FINISHED |
| Object | Collonges |
E368546
|
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: Collonges | Statement: [Thoiry, hasBorderingCommune, Collonges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Collonges Context triple: [Thoiry, hasBorderingCommune, Collonges]
-
A.
Collonges
chosen
Collonges is a commune in eastern France located within the Ain department near the Swiss border.
-
B.
Collonge
Collonge is a locality within the municipality of Collonge-Bellerive in the canton of Geneva, Switzerland.
-
C.
Sassenage
Sassenage is a commune in southeastern France near Grenoble, known for its historic château, caves, and scenic setting at the foot of the Vercors massif.
-
D.
Olbreuse
Olbreuse is a small locality in western France historically notable as the ancestral seat of the noble d’Olbreuse family.
-
E.
Aiguillon
Aiguillon is a commune in southwestern France, known for its strategic location at the confluence of the Lot and Garonne rivers.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab6abbc8190a4971ad5a654b0cd |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fdc835081909772f3a3aaee538f |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:53 p.m.