Triple
T2812163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonne department |
E54195
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Joigny |
E286507
|
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: Joigny | Statement: [Yonne department, contains, Joigny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joigny Context triple: [Yonne department, contains, Joigny]
-
A.
Joigny
chosen
Joigny is a historic commune in north-central France known for its medieval architecture and vineyards along the Yonne River.
-
B.
Givry
Givry is a Burgundy wine appellation in eastern France, noted for its predominantly Pinot Noir red wines with a reputation for good value and quality.
-
C.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
-
D.
Brière
Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
-
E.
Remigny
Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde354a5881908cd3d545f7dda81c |
completed | March 7, 2026, 8:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402b005d88190b127d483ee48c2cd |
completed | March 13, 2026, 12:27 p.m. |
Created at: March 6, 2026, 9:59 p.m.