Triple
T25605995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Right |
E641913
|
entity |
| Predicate | usesSampleOrInterpolation |
P91539
|
FINISHED |
| Object | Soul Power |
—
|
NE NERFINISHED |
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: Soul Power | Statement: [Get Right, usesSampleOrInterpolation, Soul Power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSampleOrInterpolation Context triple: [Get Right, usesSampleOrInterpolation, Soul Power]
-
A.
usesSamplingOrInterpolation
chosen
Indicates that one entity applies sampling or interpolation techniques to obtain or approximate values from another entity or dataset.
-
B.
usesInterpolationFrom
Indicates that one entity derives or computes its values by applying interpolation based on data or parameters obtained from another entity.
-
C.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
D.
supportsInterpolation
Indicates that one entity provides the capability to perform interpolation operations on another entity or its data.
-
E.
hasInterpolation
Indicates that one value, state, or representation is derived from others by applying an interpolation method between them.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 21, 2026, 4:38 p.m.