Triple
T10394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English |
E211
|
entity |
| Predicate | hasStandardizationBody |
P1251
|
FINISHED |
| Object | no single official regulatory body |
—
|
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: no single official regulatory body | Statement: [English, hasStandardizationBody, no single official regulatory body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardizationBody Context triple: [English, hasStandardizationBody, no single official regulatory body]
-
A.
notableStandard
Indicates that one entity is a widely recognized or influential standard that the other entity is associated with or exemplifies.
-
B.
hasOrganizationalStructure
Indicates that an entity possesses a defined internal arrangement of roles, responsibilities, and relationships that determine how it is organized and operates.
-
C.
hasISOCode
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
D.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
E.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242cce40481908e5eae0c94313c25 |
completed | Feb. 28, 2026, 1:20 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.