Triple
T179969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLP |
E3850
|
entity |
| Predicate | minorUnitUsage |
P7043
|
FINISHED |
| Object | not in practice |
—
|
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: not in practice | Statement: [CLP, minorUnitUsage, not in practice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minorUnitUsage Context triple: [CLP, minorUnitUsage, not in practice]
-
A.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
B.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
-
C.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
-
D.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
E.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
- F. None of above. chosen
Provenance (4 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25901a9188190b8f510bec8c8e7f2 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.