Triple
T27616160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 25040 |
E700442
|
entity |
| Predicate | usesQualityModelFrom |
P50251
|
FINISHED |
| Object | ISO/IEC 25010 |
—
|
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: ISO/IEC 25010 | Statement: [ISO/IEC 25040, usesQualityModelFrom, ISO/IEC 25010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesQualityModelFrom Context triple: [ISO/IEC 25040, usesQualityModelFrom, ISO/IEC 25010]
-
A.
hasQualityAssuranceModel
Indicates that an entity is associated with or governed by a specific quality assurance model or framework.
-
B.
supportsQuality
Indicates that one entity contributes to maintaining, enhancing, or ensuring the quality or standard of another entity or process.
-
C.
hasQualityCriterion
chosen
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
D.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
-
E.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f630d7de8c8190be167b89f6e54823 |
completed | May 2, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:12 p.m.