Triple
T38171946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carbonne |
E1000096
|
entity |
| Predicate | watercourseTypeNearby |
P8567
|
FINISHED |
| Object | major river (Garonne) |
—
|
LITERAL 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: major river (Garonne) | Statement: [Carbonne, watercourseTypeNearby, major river (Garonne)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: watercourseTypeNearby Context triple: [Carbonne, watercourseTypeNearby, major river (Garonne)]
-
A.
riverTypeNearby
Indicates that one entity is located near a river of a specified type or classification.
-
B.
nearbyWatercourse
chosen
Indicates that one entity is located close to or alongside a natural or artificial watercourse, such as a river, stream, or canal.
-
C.
nearbyRiverProject
Indicates that there is a project located close to or associated with a nearby river.
-
D.
nearbyWaterfall
Indicates that the entity is located close to or within a short distance of a waterfall.
-
E.
watercourseFeature
Indicates that a feature is a physical characteristic or component associated with a watercourse (such as a river, stream, or canal).
- F. None of above.
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_69f76daaace48190a38cee37f8ce343f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe7eb4b8348190bb19d35766189ed4 |
completed | May 9, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69fe7c35d2148190ab952e54feda1e76 |
completed | May 9, 2026, 12:13 a.m. |
Created at: May 3, 2026, 4:29 p.m.