Triple

T1612297
Position Surface form Disambiguated ID Type / Status
Subject Common Language Runtime E34639 entity
Predicate supportsLanguage P2177 FINISHED
Object IronPython E97047 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: IronPython | Statement: [Common Language Runtime, supportsLanguage, IronPython]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IronPython
Context triple: [Common Language Runtime, supportsLanguage, IronPython]
  • A. IronPython chosen
    IronPython is an implementation of the Python programming language that runs on the .NET framework, allowing Python code to interoperate seamlessly with .NET libraries and applications.
  • B. Jython
    Jython is an implementation of the Python programming language that runs on the Java platform and allows seamless integration with Java code and libraries.
  • 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. Cython
    Cython is a programming language and compiler that extends Python with static typing and direct C/C++ integration to generate fast, optimized extension modules.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9098cd03081908c67f95fd54d2071 completed March 5, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51c751308190a89f6462ee365418 completed March 8, 2026, 10:39 a.m.
Created at: March 4, 2026, 7:28 p.m.