Triple
T34614735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.7 |
E888830
|
entity |
| Predicate | hasStandardLibraryModule |
P12988
|
FINISHED |
| Object | dataclasses |
—
|
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: dataclasses | Statement: [Python 3.7, hasStandardLibraryModule, dataclasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardLibraryModule Context triple: [Python 3.7, hasStandardLibraryModule, dataclasses]
-
A.
hasOfficialLibrary
Indicates that an entity possesses or is served by a formally recognized, authorized library.
-
B.
hasModuleConstruct
chosen
Indicates that an entity includes, defines, or is composed of a specific module as one of its structural or functional components.
-
C.
hasLibraries
Indicates that an entity possesses, contains, or is associated with one or more libraries.
-
D.
hasModulePath
Indicates that something is associated with or identified by a specific module path within a modular or hierarchical structure.
-
E.
hasStandardImplementation
Indicates that an entity has a defined, commonly accepted implementation that follows an established standard or specification.
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffacdf9f5c8190baef0245edfe87fc |
completed | May 9, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69ffac5e86e08190a1e6da0840a237ad |
completed | May 9, 2026, 9:51 p.m. |
Created at: May 1, 2026, 2:03 a.m.