Triple
T215694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allier department |
E4815
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Montluçon |
E52473
|
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: Montluçon | Statement: [Allier department, largestCity, Montluçon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montluçon Context triple: [Allier department, largestCity, Montluçon]
-
A.
Montluçon
chosen
Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
-
B.
Châteauroux
Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
-
C.
Clermont-Ferrand
Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
-
D.
Brive-la-Gaillarde
Brive-la-Gaillarde is a historic town in the Corrèze department of south-central France, known for its medieval architecture, vibrant market culture, and role as a regional economic center.
-
E.
Fronsac
Fronsac is a French wine appellation on the right bank of the Dordogne River, known for its Merlot-based red wines and proximity to Bordeaux.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c4ca0c8819093f63c6371e2d140 |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4253cbdb88190a4db08c9a91bc15a |
completed | March 1, 2026, 11:38 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.