Triple
T10763885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.10 |
E253903
|
entity |
| Predicate | precededBy |
P97
|
FINISHED |
| Object | Python 3.9 |
E884131
|
NE 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: Python 3.9 | Statement: [Python 3.10, precededBy, Python 3.9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python 3.9 Context triple: [Python 3.10, precededBy, Python 3.9]
-
A.
Python 3.9
chosen
Python 3.9 is a stable release of the Python programming language that introduced features like dictionary union operators, type hinting improvements, and new string methods before being succeeded by Python 3.10.
-
B.
Python 3.10
Python 3.10 is a major release of the Python programming language that introduced structural pattern matching and various syntax and performance improvements.
-
C.
Python 3.8
Python 3.8 is a major release of the Python programming language that introduced several new language features, performance improvements, and standard library enhancements.
-
D.
Pythonidae
Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
-
E.
PEP 634
PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a504948190943f0e27c0d891ed |
completed | April 9, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de55bb98ec8190914031643c1c7a97 |
completed | April 14, 2026, 2:56 p.m. |
Created at: April 8, 2026, 9:16 p.m.