Triple
T18240729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lierelva |
E436800
|
entity |
| Predicate | hasMouthInMunicipality |
P32498
|
FINISHED |
| Object | Drammen municipality |
—
|
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: Drammen municipality | Statement: [Lierelva, hasMouthInMunicipality, Drammen municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMouthInMunicipality Context triple: [Lierelva, hasMouthInMunicipality, Drammen municipality]
-
A.
mouthLocatedInAdministrativeEntity
chosen
Indicates that the place where a river ends (its mouth) is situated within a specific administrative region or jurisdiction.
-
B.
containsMouthOf
Indicates that one entity geographically includes or encompasses the mouth (outflow point) of another entity, such as a river or stream.
-
C.
hasMouthPositionRelativeToCity
Indicates the spatial position of a river’s mouth in relation to a specified city.
-
D.
hasNameInMunicipality
Indicates that an entity is known by a particular name within the context or jurisdiction of a specific municipality.
-
E.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e287548190b666a990e5b168b0 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:33 a.m.