Triple
T27316117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copper Mountain Resort |
E689351
|
entity |
| Predicate | terrainDivision |
P139903
|
FINISHED |
| Object | beginner terrain in West Village |
—
|
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: beginner terrain in West Village | Statement: [Copper Mountain Resort, terrainDivision, beginner terrain in West Village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainDivision Context triple: [Copper Mountain Resort, terrainDivision, beginner terrain in West Village]
-
A.
fieldDivision
Indicates a relationship where a larger field or area is partitioned into smaller sections or subdivisions.
-
B.
terrainIncludes
Indicates that a specified terrain area contains or encompasses another geographic or environmental feature within its boundaries.
-
C.
dimensionSplit
Indicates that a single dimension or measure is divided into multiple separate components or sub-dimensions.
-
D.
typicalDivision
chosen
Indicates that one entity is a standard or characteristic subdivision or component of another entity.
-
E.
subdivisionFactor
Indicates how many smaller parts or segments a whole entity is divided into within a given context.
- 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_69ef355c53a08190a8a92e355a7ce115 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f627b69d0881908e5da0d2d6acedae |
completed | May 2, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69f620e4b1c88190a17940251abc68fd |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 11:30 a.m.