Triple
T20902418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 27011 |
E514704
|
entity |
| Predicate | tailors |
P141634
|
FINISHED |
| Object | ISO/IEC 27002 controls for telecommunications |
—
|
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: ISO/IEC 27002 controls for telecommunications | Statement: [ISO/IEC 27011, tailors, ISO/IEC 27002 controls for telecommunications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tailors Context triple: [ISO/IEC 27011, tailors, ISO/IEC 27002 controls for telecommunications]
-
A.
hasNotableTailor
Indicates that an entity is associated with a tailor who is distinguished or noteworthy in some significant way.
-
B.
tailorsCreditsFor
Indicates that one party customizes or adjusts credits to suit the needs, characteristics, or context of another party.
-
C.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
D.
stylingHouse
Indicates a relationship where a house is being designed, decorated, or otherwise given a particular aesthetic style.
-
E.
typicalWear
Indicates that one entity is commonly or characteristically worn by the other in typical situations or contexts.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8fd7e4481909088b7f74ba24549 |
completed | April 21, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53d22d08190bc17ed4bed53804a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:47 p.m.