Triple
T31699762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calore Irpino |
E809019
|
entity |
| Predicate | mouthLocatedInRegion |
P101073
|
FINISHED |
| Object | Campania |
—
|
NE NERFINISHED |
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: Campania | Statement: [Calore Irpino, mouthLocatedInRegion, Campania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mouthLocatedInRegion Context triple: [Calore Irpino, mouthLocatedInRegion, Campania]
-
A.
mouthLocatedInAdministrativeEntity
Indicates that the place where a river ends (its mouth) is situated within a specific administrative region or jurisdiction.
-
B.
mouthOf
Indicates the location where one entity (typically a river or similar feature) empties into or opens out into another, larger body or feature.
-
C.
mouthCountrySubdivision
chosen
Indicates the country subdivision (such as a state or province) in which the mouth or endpoint of a geographic feature (typically a river) is located.
-
D.
mouthNear
Indicates that one entity’s mouth is positioned close to another entity or object in space.
-
E.
containsMouthOf
Indicates that one entity geographically includes or encompasses the mouth (outflow point) of another entity, such as a river or stream.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:11 p.m.