Triple
T8288217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gdi32 |
E193832
|
entity |
| Predicate | hasFileName |
P33859
|
FINISHED |
| Object | gdi32.dll |
—
|
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: gdi32.dll | Statement: [Gdi32, hasFileName, gdi32.dll]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFileName Context triple: [Gdi32, hasFileName, gdi32.dll]
-
A.
hasFileExtension
Indicates that one entity (typically a file) possesses a specific file extension denoting its type or format.
-
B.
fileName
chosen
Indicates the name assigned to a file, typically used to identify or reference that file within a system or context.
-
C.
hasDataFile
Indicates that an entity is associated with or linked to a specific data file that stores its related information.
-
D.
hasFileFormat
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.
-
E.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
- 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c98e15c8190ac2a0b2a5ff834c9 |
completed | March 31, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:52 p.m.