Triple
T10763941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standards Track |
E253904
|
entity |
| Predicate | hasSubcategory |
P747
|
FINISHED |
| Object | Language PEP |
E605134
|
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: Language PEP | Statement: [Standards Track, hasSubcategory, Language PEP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Language PEP Context triple: [Standards Track, hasSubcategory, Language PEP]
-
A.
PEP
PEP is the stock ticker symbol for PepsiCo, the multinational food, snack, and beverage corporation traded on the NASDAQ.
-
B.
PEPM
PEPM (Partial Evaluation and Program Manipulation) is an ACM SIGPLAN-sponsored symposium focused on research in program analysis, transformation, and generation techniques.
-
C.
PEP 0
PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
-
D.
Papel language
chosen
Papel language is a Niger–Congo language spoken by the Pepel people, primarily in Guinea-Bissau in West Africa.
-
E.
PEP 1
PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
- 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_69de235fe7748190ba004f889da389ff |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.