Triple
T29866922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STEP |
E758484
|
entity |
| Predicate | dataModelLanguageStandard |
P167686
|
FINISHED |
| Object | ISO 10303-11 |
—
|
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 10303-11 | Statement: [STEP, dataModelLanguageStandard, ISO 10303-11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataModelLanguageStandard Context triple: [STEP, dataModelLanguageStandard, ISO 10303-11]
-
A.
dataModelLanguage
chosen
Indicates that one entity is a language or formalism used to define, describe, or structure the data model of another entity.
-
B.
standardLanguageBasisFor
Indicates that one language serves as the normative or reference standard upon which another language variety, form, or usage is based.
-
C.
sharedLanguageStandard
Indicates that the related entities use or conform to the same language standard or specification.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
majorStandardLanguage
Indicates that a language is the primary or most widely used standard language associated with an entity (such as a country, region, or group).
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6768a6b348190a88b3aa787249cb3 |
completed | May 2, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 5:52 p.m.