Triple
T1719053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PowerShell |
E37350
|
entity |
| Predicate | usesDataFormat |
P8462
|
FINISHED |
| Object | objects |
—
|
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: objects | Statement: [PowerShell, usesDataFormat, objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDataFormat Context triple: [PowerShell, usesDataFormat, objects]
-
A.
usedDataFrom
Indicates that one entity utilized or relied on data originating from another entity.
-
B.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
C.
hasFileFormat
chosen
Indicates that one entity (typically a digital file or resource) is encoded, stored, or represented using a specific file format defined by the other entity.
-
D.
dataUse
Indicates how data is intended to be accessed, processed, or applied within a particular context or activity.
-
E.
featuresFormat
Indicates that something (such as a product, service, or medium) is presented, delivered, or made available in a particular format or configuration.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab5c96db6c8190a745d6fef7bf2cdb |
completed | March 6, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69aa61bed2fc819086d912cd34285978 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.