Triple
T14843940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picard |
E349035
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Tournaisien
Tournaisien is a regional variety of the Picard language traditionally spoken in and around the city of Tournai in Belgium.
|
E1126208
|
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: Tournaisien | Statement: [Picard, hasDialect, Tournaisien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tournaisien Context triple: [Picard, hasDialect, Tournaisien]
-
A.
Valenciennes
Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
-
B.
Oissel
Oissel is a commune in the Seine-Maritime department of the Normandy region in northern France, situated near the city of Rouen.
-
C.
Montargis
Montargis is a historic market town in north-central France, known for its canals, medieval architecture, and traditional praline confectionery.
-
D.
Yvoir
Yvoir is a small municipality and village in the Walloon region of Belgium, known for its scenic location along the Meuse River.
-
E.
Dinant
Dinant is a picturesque Belgian town in Wallonia known for its dramatic cliffs along the Meuse River, its citadel, and as the birthplace of saxophone inventor Adolphe Sax.
- 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: Tournaisien Triple: [Picard, hasDialect, Tournaisien]
Generated description
Tournaisien is a regional variety of the Picard language traditionally spoken in and around the city of Tournai in Belgium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tournaisien Target entity description: Tournaisien is a regional variety of the Picard language traditionally spoken in and around the city of Tournai in Belgium.
-
A.
Valenciennes
Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
-
B.
Oissel
Oissel is a commune in the Seine-Maritime department of the Normandy region in northern France, situated near the city of Rouen.
-
C.
Montargis
Montargis is a historic market town in north-central France, known for its canals, medieval architecture, and traditional praline confectionery.
-
D.
Yvoir
Yvoir is a small municipality and village in the Walloon region of Belgium, known for its scenic location along the Meuse River.
-
E.
Dinant
Dinant is a picturesque Belgian town in Wallonia known for its dramatic cliffs along the Meuse River, its citadel, and as the birthplace of saxophone inventor Adolphe Sax.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded291103c8190a64cfe700bfee197 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b4b31a48190a3b60f02b581fbd2 |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6f49da9081909ba2b75d9a370a34 |
completed | May 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6fa989e4819092858dd24c97eee0 |
completed | May 8, 2026, 11:20 p.m. |
Created at: April 10, 2026, 1:53 a.m.