Triple
T10818160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 635 |
E255288
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | PEP 634 |
E253900
|
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: PEP 634 | Statement: [PEP 635, relatedTo, PEP 634]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP 634 Context triple: [PEP 635, relatedTo, PEP 634]
-
A.
PEP 634
chosen
PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
-
B.
PEP 636
PEP 636 is a Python Enhancement Proposal that serves as a tutorial-style guide to the structural pattern matching feature introduced in Python 3.10.
-
C.
PEP 635
PEP 635 is a Python Enhancement Proposal that provides a detailed rationale and motivation for the structural pattern matching feature introduced in Python 3.10.
-
D.
PEP 624
PEP 624 is a Python Enhancement Proposal that specifies the removal of the Py_UNICODE encoder APIs from the CPython C API to streamline and modernize Unicode handling in Python.
-
E.
PEP 649
PEP 649 is a Python enhancement proposal that introduces a new, lazy evaluation scheme for type annotations to improve performance and forward-reference handling.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7344866f88190be4addb7c8020fce |
completed | April 9, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e55621a88c8190b9611bf9e3b307de |
completed | April 19, 2026, 10:24 p.m. |
Created at: April 8, 2026, 9:18 p.m.