Triple
T2530376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cévennes |
E56142
|
entity |
| Predicate | notableTown |
P14082
|
FINISHED |
| Object |
Le Vigan
Le Vigan is a historic market town in southern France that serves as one of the main gateways to the Cévennes mountain region.
|
E275524
|
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: Le Vigan | Statement: [Cévennes, notableTown, Le Vigan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Vigan Context triple: [Cévennes, notableTown, Le Vigan]
-
A.
Vavin
Vavin is a Paris Métro station in the 6th arrondissement, serving the Montparnasse and Jardin du Luxembourg area.
-
B.
Juliénas
Juliénas is a French wine appellation in the northern Beaujolais region, known for its structured, aromatic red wines primarily made from the Gamay grape.
-
C.
Viré
Viré is a renowned wine-producing village in France’s Mâconnais region, best known for its high-quality white Burgundy wines made primarily from Chardonnay.
-
D.
Yssingeaux
Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
-
E.
Le Lavandou
Le Lavandou is a seaside resort town on the French Riviera in southeastern France, known for its sandy beaches and Mediterranean coastal scenery.
- 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: Le Vigan Triple: [Cévennes, notableTown, Le Vigan]
Generated description
Le Vigan is a historic market town in southern France that serves as one of the main gateways to the Cévennes mountain region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Le Vigan Target entity description: Le Vigan is a historic market town in southern France that serves as one of the main gateways to the Cévennes mountain region.
-
A.
Vavin
Vavin is a Paris Métro station in the 6th arrondissement, serving the Montparnasse and Jardin du Luxembourg area.
-
B.
Juliénas
Juliénas is a French wine appellation in the northern Beaujolais region, known for its structured, aromatic red wines primarily made from the Gamay grape.
-
C.
Viré
Viré is a renowned wine-producing village in France’s Mâconnais region, best known for its high-quality white Burgundy wines made primarily from Chardonnay.
-
D.
Yssingeaux
Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
-
E.
Le Lavandou
Le Lavandou is a seaside resort town on the French Riviera in southeastern France, known for its sandy beaches and Mediterranean coastal scenery.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd276930c8190bd46b52e06b7098e |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2bb6bb608190845706f1a675ad1c |
completed | March 9, 2026, 8:21 p.m. |
| NEDg | Description generation | batch_69af51dee3508190a0d1608a7d905742 |
completed | March 9, 2026, 11:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af52a97d008190b55491fa557eb729 |
completed | March 9, 2026, 11:07 p.m. |
Created at: March 6, 2026, 9:46 p.m.