Triple
T10763769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Structural Pattern Matching |
E253899
|
entity |
| Predicate | hasSemanticsSpecifiedIn |
P74447
|
FINISHED |
| Object | PEP 634 |
E253900
|
NE FINISHED |
How this triple was built (3 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: [Structural Pattern Matching, hasSemanticsSpecifiedIn, PEP 634]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP 634 Context triple: [Structural Pattern Matching, hasSemanticsSpecifiedIn, 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 695
PEP 695 is a Python Enhancement Proposal that introduces a new, more concise syntax for type parameter declarations to improve the language’s support for generics and static typing.
-
E.
PEP 622
PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSemanticsSpecifiedIn Context triple: [Structural Pattern Matching, hasSemanticsSpecifiedIn, PEP 634]
-
A.
hasSemantics
Indicates that one entity carries or encodes the meaning, interpretation, or semantic content associated with another entity.
-
B.
hasSemanticsDefinedBy
chosen
Indicates that the meaning or interpretation of one entity is specified, constrained, or determined by another entity.
-
C.
hasSemanticRestriction
Indicates that a concept or relation is constrained in meaning or usage by specific semantic conditions or limitations.
-
D.
hasSpecification
Indicates that an entity is associated with a particular specification that defines or constrains its properties, behavior, or requirements.
-
E.
hasSpecificationSection
Indicates that an entity includes or is associated with a particular section dedicated to specifications.
- F. None of above.
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. |
| NED1 | Entity disambiguation (via context triple) | batch_69de84b88ba08190afddea2976d12465 |
completed | April 14, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.