Triple

T10946341
Position Surface form Disambiguated ID Type / Status
Subject Standards Track PEPs E258606 entity
Predicate appliesTo P1129 FINISHED
Object Python programming language E3372 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: Python programming language | Statement: [Standards Track PEPs, appliesTo, Python programming language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python programming language
Context triple: [Standards Track PEPs, appliesTo, Python programming language]
  • A. Python
    Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
  • B. Python chosen
    Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
  • C. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • D. PyPy
    PyPy is a high-performance alternative Python interpreter featuring a Just-In-Time (JIT) compiler designed to significantly speed up the execution of Python programs.
  • E. Python 3.x
    Python 3.x is the major, actively developed series of the Python programming language that introduced significant improvements and changes over Python 2, including cleaner syntax, better Unicode support, and a more consistent standard library.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770eaaea08190b06e508600d8a305 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3446b6f1481908365bb9235768859 completed April 18, 2026, 8:44 a.m.
Created at: April 8, 2026, 9:23 p.m.