Triple
T127192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBI Theater |
E2575
|
entity |
| Predicate | terrainCharacteristic |
P1094
|
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: [CBI Theater, terrainCharacteristic, mountainous terrain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainCharacteristic Context triple: [CBI Theater, terrainCharacteristic, mountainous terrain]
-
A.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
B.
surfaceType
Indicates the kind or classification of surface associated with an entity or interaction.
-
C.
hasNaturalFeature
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
D.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25761e9248190a7205bfc36cb5c45 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.