Triple
T11784519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bugey |
E280236
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object |
Montagnieu
Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
|
E957575
|
NE FINISHED |
How this triple was built (4 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: Montagnieu | Statement: [Bugey, hasSubregion, Montagnieu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montagnieu Context triple: [Bugey, hasSubregion, Montagnieu]
-
A.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
B.
Vaugier
Vaugier is the surname of Emmanuelle Vaugier, a Canadian actress and model known for roles in television series such as "Two and a Half Men" and "Smallville."
-
C.
Moreuil
Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
-
D.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
E.
Longjumeau
Longjumeau is a suburban commune in the southern outskirts of Paris, France, known for its residential character and proximity to major transport routes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Montagnieu Triple: [Bugey, hasSubregion, Montagnieu]
Generated description
Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Montagnieu Target entity description: Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
-
A.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
B.
Vaugier
Vaugier is the surname of Emmanuelle Vaugier, a Canadian actress and model known for roles in television series such as "Two and a Half Men" and "Smallville."
-
C.
Moreuil
Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
-
D.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
E.
Longjumeau
Longjumeau is a suburban commune in the southern outskirts of Paris, France, known for its residential character and proximity to major transport routes.
- F. None of above. chosen
Provenance (5 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_69d8a585795c8190aa8a5edf0d99b47f |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4713ee6e48190ab1860b9899b7b48 |
completed | May 1, 2026, 9:24 a.m. |
| NEDg | Description generation | batch_69f47b755f808190acb2fb31473d2405 |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47d8bbae8819088d48b300291ef74 |
completed | May 1, 2026, 10:16 a.m. |
Created at: April 8, 2026, 9:42 p.m.