Triple
T10851824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.8 |
E256163
|
entity |
| Predicate | hasModuleChange |
P96072
|
FINISHED |
| Object | statistics module enhancements |
—
|
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: statistics module enhancements | Statement: [Python 3.8, hasModuleChange, statistics module enhancements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModuleChange Context triple: [Python 3.8, hasModuleChange, statistics module enhancements]
-
A.
hasModuleConstruct
Indicates that an entity includes, defines, or is composed of a specific module as one of its structural or functional components.
-
B.
hasChangeControl
Indicates that an entity is subject to a defined process for reviewing, approving, and managing modifications or updates.
-
C.
hasResultingChange
Indicates that one entity causes or leads to a specific change or transformation in another entity or state.
-
D.
hasHumanModification
Indicates that an entity has been altered, influenced, or modified as a result of human activity or intervention.
-
E.
hasDesignChange
Indicates that an entity has undergone a modification or alteration to its original design.
- F. None of above. chosen
Provenance (4 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75117b76c8190b0fb216b1428c3c7 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:20 p.m.