Triple
T9204081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kacha River |
E220924
|
entity |
| Predicate | hasLandscapeTypeAlongCourse |
P7342
|
FINISHED |
| Object | mountainous terrain |
—
|
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: mountainous terrain | Statement: [Kacha River, hasLandscapeTypeAlongCourse, mountainous terrain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeTypeAlongCourse Context triple: [Kacha River, hasLandscapeTypeAlongCourse, mountainous terrain]
-
A.
hasLandscapeType
chosen
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasProtectedAreaAlongCourse
Indicates that a segment of the course or route passes through or borders a designated protected area.
-
D.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
E.
hasRacecourseFeature
Indicates that something possesses or includes a specific feature or characteristic related to a racecourse.
- 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_69ca83e8e9248190862cf3e41693b310 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd945f37881909f0d30eeb6a7a3ad |
completed | April 1, 2026, 8:37 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:26 p.m.