Triple
T10763913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.10 |
E253903
|
entity |
| Predicate | hasTypingFeature |
P95862
|
FINISHED |
| Object | PEP 604 union types with | operator |
—
|
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: PEP 604 union types with | operator | Statement: [Python 3.10, hasTypingFeature, PEP 604 union types with | operator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypingFeature Context triple: [Python 3.10, hasTypingFeature, PEP 604 union types with | operator]
-
A.
hasKeyboard
Indicates that one entity possesses or is equipped with a keyboard as a component or accessory.
-
B.
keyboardFeature
Indicates that one entity is a feature, characteristic, or functional attribute of a keyboard.
-
C.
hasFunctionKeys
Indicates that an object or device possesses dedicated keys assigned to specific functions or shortcuts.
-
D.
keyHitter
Indicates that an entity is a powerful or highly effective performer, especially in a competitive or performance-based context.
-
E.
hasTypography
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a504948190943f0e27c0d891ed |
completed | April 9, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.