Triple
T24813592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Script Editor (macOS) |
E620853
|
entity |
| Predicate | fileTypeSupported |
P24486
|
FINISHED |
| Object | .scpt |
—
|
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: .scpt | Statement: [Script Editor (macOS), fileTypeSupported, .scpt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fileTypeSupported Context triple: [Script Editor (macOS), fileTypeSupported, .scpt]
-
A.
fileTypeCode
Indicates the specific classification or category code that identifies the type or format of a file.
-
B.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
C.
typicalFileType
Indicates that one entity is the usual or commonly associated file type for the other entity.
-
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.
filenameType
Indicates the type or category associated with a given filename (e.g., file format, role, or classification).
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:59 a.m.