Triple

T36657024
Position Surface form Disambiguated ID Type / Status
Subject PEP 614 E905021 entity
Predicate hasTitle P38 FINISHED
Object Relaxing Grammar Restrictions On Decorators
"Relaxing Grammar Restrictions On Decorators" is a Python Enhancement Proposal (PEP 614) that broadens the syntax rules for decorators to allow more flexible and expressive decorator expressions in Python code.
E2193276 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: Relaxing Grammar Restrictions On Decorators | Statement: [PEP 614, hasTitle, Relaxing Grammar Restrictions On Decorators]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Relaxing Grammar Restrictions On Decorators
Triple: [PEP 614, hasTitle, Relaxing Grammar Restrictions On Decorators]
Generated description
"Relaxing Grammar Restrictions On Decorators" is a Python Enhancement Proposal (PEP 614) that broadens the syntax rules for decorators to allow more flexible and expressive decorator expressions in Python code.

Provenance (5 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_69f76e6e3b908190970251b30f76ad71 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c77907808190904959e4326fed7d completed May 3, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20cead00819094ef6393f7bd43d1 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a21d045cc81908d61119fb621f7b6 completed June 23, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a3a225b99788190bafbd7ccb4a652b9 completed June 23, 2026, 6:06 a.m.
Created at: May 3, 2026, 4:11 p.m.