Triple
T15181452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loup |
E362753
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Cagne |
E591877
|
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: Cagne | Statement: [Loup, hasTributary, Cagne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cagne Context triple: [Loup, hasTributary, Cagne]
-
A.
Cagne
chosen
The Cagne is a small coastal river in southeastern France that flows through the town of Cagnes-sur-Mer into the Mediterranean Sea.
-
B.
Gouet
Gouet is an old French white grape variety, better known as Gouais Blanc, historically used in Europe and notable as a parent of many classic wine grapes.
-
C.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
-
D.
Canet
Canet is a French surname most notably borne by actor and filmmaker Guillaume Canet.
-
E.
Corcelette
Corcelette is a renowned vineyard site in the Morgon appellation of Beaujolais, known for producing structured, age-worthy Gamay wines.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006663ad48190986b680001be0e9b |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed32a1e3c81909ca2bd431a01e9cf |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:09 a.m.