Triple

T10547121
Position Surface form Disambiguated ID Type / Status
Subject Damien P. George E248849 entity
Predicate inspiredBy P9 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: [Damien P. George, inspiredBy, Python (programming language)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python (programming language)
Context triple: [Damien P. George, inspiredBy, Python (programming language)]
  • A. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • B. Python
    Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
  • C. Python chosen
    Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
  • 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. Repyt
    Repyt is an ancient Egyptian lioness goddess primarily worshipped at Akhmim, associated with protection and sometimes linked to solar and warlike aspects.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d20ef48190ab9f70d4ce5f2a11 completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9344a53fc81909765061d07d0cd20 completed April 10, 2026, 5:32 p.m.
Created at: April 6, 2026, 12:33 p.m.