Triple
T35932417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake District foothills |
E1039200
|
entity |
| Predicate | terrainGradient |
P101500
|
FINISHED |
| Object | gentle slopes |
—
|
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: gentle slopes | Statement: [Lake District foothills, terrainGradient, gentle slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainGradient Context triple: [Lake District foothills, terrainGradient, gentle slopes]
-
A.
terrainStyle
chosen
Indicates the characteristic type or pattern of terrain associated with an entity or location.
-
B.
terrainMode
Indicates that an entity operates or is configured in a specific terrain-related mode or setting.
-
C.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
D.
terrainMaterial
Indicates the type of physical surface or ground substance that composes a given terrain.
-
E.
terrainSpecialization
Indicates a relationship where an entity is particularly adapted or optimized for operation, performance, or use within a specific type of terrain.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.