Triple
T7896395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 25010 |
E183351
|
entity |
| Predicate | hasSubCharacteristic |
P21666
|
FINISHED |
| Object | functional completeness |
—
|
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: functional completeness | Statement: [ISO/IEC 25010, hasSubCharacteristic, functional completeness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubCharacteristic Context triple: [ISO/IEC 25010, hasSubCharacteristic, functional completeness]
-
A.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
eraCharacteristic
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given historical or temporal era.
-
C.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
D.
describesCharacteristicOf
Indicates that one entity expresses or specifies a characteristic, feature, or property of another entity.
-
E.
hasSubConcept
chosen
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a187a0081909a0c0822c6dab1da |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:01 p.m.