Triple
T17557566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TOML |
E427624
|
entity |
| Predicate | typicalFileName |
P33859
|
FINISHED |
| Object | pyproject.toml |
—
|
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: pyproject.toml | Statement: [TOML, typicalFileName, pyproject.toml]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFileName Context triple: [TOML, typicalFileName, pyproject.toml]
-
A.
typicalFileType
Indicates that one entity is the usual or commonly associated file type for the other entity.
-
B.
typicalFileFormat
Indicates the usual or standard file format typically associated with or used for a given entity or context.
-
C.
fileName
chosen
Indicates the name assigned to a file, typically used to identify or reference that file within a system or context.
-
D.
typicalEntryFile
Indicates that a given file is the standard or primary entry point typically used to start or access something (such as a program, project, or package).
-
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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4562413d08190acaa5272046d3626 |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.