Triple
T2812161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonne department |
E54195
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sens |
E225980
|
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: Sens | Statement: [Yonne department, contains, Sens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sens Context triple: [Yonne department, contains, Sens]
-
A.
Sens
chosen
Sens is a historic commune in north-central France known for its impressive Gothic cathedral and role as a regional administrative and commercial center.
-
B.
Senne
The Senne is a small river flowing through Brussels, Belgium, much of which has been covered over as the city developed.
-
C.
Sinn
Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia region.
-
D.
Sinte
Sinte is an alternative self-designation used by the Sinti, a subgroup of the Romani people primarily found in Central Europe.
-
E.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
- 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_69afe8aecd5081909b38d229904e5bde |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 9:59 p.m.