Triple
T2320972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP 1 |
E51178
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | PEP Purpose and Guidelines |
E51178
|
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 Purpose and Guidelines | Statement: [PEP 1, title, PEP Purpose and Guidelines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP Purpose and Guidelines Context triple: [PEP 1, title, PEP Purpose and Guidelines]
-
A.
PEPs
PEPs are formal design documents that propose and describe new features, processes, or changes for the Python programming language and its community.
-
B.
PEP 0
PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
-
C.
PEP 1
chosen
PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
-
D.
PEP 13
PEP 13 is the Python Enhancement Proposal that defines the process and rules for selecting and operating the Python Steering Council, the core governance body of the Python project.
-
E.
Process PEP
A Process PEP is a type of Python Enhancement Proposal that defines or changes procedures, workflows, and governance practices for the Python community rather than the language or its implementation.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc632474c8190972b4611a3a4ff8f |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae896911908190b53954dbf854cc18 |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:49 p.m.