Triple
T7933669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenDocument format |
E184239
|
entity |
| Predicate | vendorNeutral |
P52982
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [OpenDocument format, vendorNeutral, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vendorNeutral Context triple: [OpenDocument format, vendorNeutral, true]
-
A.
platformNeutral
Indicates that something is compatible with, applicable to, or designed to work across multiple platforms without dependence on any specific one.
-
B.
isVendorNeutral
chosen
Indicates that something is not biased toward, affiliated with, or dependent on any particular vendor or supplier.
-
C.
languageNeutral
Indicates that the relationship or action is independent of any specific natural language, applying uniformly across different linguistic contexts.
-
D.
usesNeutral
Indicates that one entity employs or applies something in a neutral, unbiased, or non-aligned manner toward another entity or context.
-
E.
vendorSpecificTo
Indicates that something is tailored, restricted, or applicable only to a particular vendor or supplier, and not generally applicable across others.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aeb132c8190bea4906aaf51b869 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.