Triple
T18799377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | xarray |
E459722
|
entity |
| Predicate | supportsDimensionType |
P56537
|
FINISHED |
| Object | time |
—
|
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: time | Statement: [xarray, supportsDimensionType, time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDimensionType Context triple: [xarray, supportsDimensionType, time]
-
A.
supportsDimensionArgument
chosen
Indicates that one entity can accept or work with another entity as a dimension-related argument in an operation or context.
-
B.
supportsType
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
C.
includesDimension
Indicates that one entity encompasses or contains a particular dimension or measurable aspect as part of its definition or structure.
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02273b481909bc250144a0ace32 |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.