Triple
T12098644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman language |
E288133
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Cauchois
Cauchois is a regional variety of the Norman language traditionally spoken in the Pays de Caux area of Normandy, France.
|
E963336
|
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: Cauchois | Statement: [Norman language, hasDialect, Cauchois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cauchois Context triple: [Norman language, hasDialect, Cauchois]
-
A.
Chénas
Chénas is a French appellation in the Beaujolais wine region known for producing structured, age-worthy red wines primarily from the Gamay grape.
-
B.
Kouroucien
Kouroucien is the French demonym for an inhabitant or native of the town of Kourou in French Guiana.
-
C.
Roisséens
Roisséens are the inhabitants of Roissy-en-France, a commune in the northeastern suburbs of Paris near Charles de Gaulle Airport.
-
D.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
E.
Angoumoisin
Angoumoisin is the French term for an inhabitant or native of the city of Angoulême in southwestern France.
- 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: Cauchois Triple: [Norman language, hasDialect, Cauchois]
Generated description
Cauchois is a regional variety of the Norman language traditionally spoken in the Pays de Caux area of Normandy, France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cauchois Target entity description: Cauchois is a regional variety of the Norman language traditionally spoken in the Pays de Caux area of Normandy, France.
-
A.
Chénas
Chénas is a French appellation in the Beaujolais wine region known for producing structured, age-worthy red wines primarily from the Gamay grape.
-
B.
Kouroucien
Kouroucien is the French demonym for an inhabitant or native of the town of Kourou in French Guiana.
-
C.
Roisséens
Roisséens are the inhabitants of Roissy-en-France, a commune in the northeastern suburbs of Paris near Charles de Gaulle Airport.
-
D.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
E.
Angoumoisin
Angoumoisin is the French term for an inhabitant or native of the city of Angoulême in southwestern France.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9155465388190bbe52453c9b11912 |
completed | April 10, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6724de481909fe29e3278136ea2 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fe53d47c8190896a9abf8cc4bc31 |
completed | May 2, 2026, 1:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5ffc2cfd08190b87eccd3a73afc77 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 8, 2026, 9:48 p.m.