Triple
T29866944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STEP |
E758484
|
entity |
| Predicate | AP242Scope |
P66989
|
FINISHED |
| Object | managed model-based 3D engineering |
—
|
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: managed model-based 3D engineering | Statement: [STEP, AP242Scope, managed model-based 3D engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AP242Scope Context triple: [STEP, AP242Scope, managed model-based 3D engineering]
-
A.
acquisitionScope
Indicates the extent, boundaries, or coverage of what is obtained or brought under control through an acquisition.
-
B.
amenityScope
Indicates the range or extent of services, facilities, or conveniences that an amenity provides or applies to.
-
C.
accessScope
Indicates the extent or boundaries of access that one entity has to another entity or resource.
-
D.
M4QScope
chosen
Indicates that one entity defines or constrains the scope, range, or applicability within which another entity or action is valid or considered.
-
E.
participantScope
Indicates the extent, range, or set of participants that are involved in or affected by a given relationship or action.
- 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_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:52 p.m.