Triple

T15264005
Position Surface form Disambiguated ID Type / Status
Subject Vyper E364852 entity
Predicate inspiredBy P9 FINISHED
Object Python 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 | Statement: [Vyper, inspiredBy, Python]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python
Context triple: [Vyper, inspiredBy, Python]
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084fed0481908e452c89cba2be82 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5fdc21881909d87062db6fb8fb7 completed May 9, 2026, 7:45 a.m.
Created at: April 10, 2026, 3:14 a.m.