Triple
T14549468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grilly |
E341375
|
entity |
| Predicate | hasBorder |
P224
|
FINISHED |
| Object | Cessy |
E395723
|
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: Cessy | Statement: [Grilly, hasBorder, Cessy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cessy Context triple: [Grilly, hasBorder, Cessy]
-
A.
Cessy
chosen
Cessy is a small commune in eastern France near the Swiss border, known for its proximity to Geneva and the CERN research center.
-
B.
Chiroubles
Chiroubles is a French appellation in the Beaujolais region known for producing light, aromatic red wines primarily from the Gamay grape.
-
C.
Guillestre
Guillestre is a small commune in southeastern France’s Hautes-Alpes department, known as a gateway to the Queyras Regional Natural Park and the surrounding Alpine valleys.
-
D.
Seyssinet-Pariset
Seyssinet-Pariset is a suburban commune in southeastern France, located in the Isère department near Grenoble at the foot of the Vercors massif.
-
E.
Cavaillon
Cavaillon is a town in southeastern France’s Vaucluse department, known for its melon production and location at the foot of the Luberon massif.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ed2b4c8190945bd26531c71f1f |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a6344b08190a3c1124c6dd7da96 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:23 a.m.