Triple

T22447254
Position Surface form Disambiguated ID Type / Status
Subject Parrot virtual machine E554891 entity
Predicate supportsLanguage P2177 FINISHED
Object Python (via Pynie and other projects) NE NERFINISHED

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 (via Pynie and other projects) | Statement: [Parrot virtual machine, supportsLanguage, Python (via Pynie and other projects)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python (via Pynie and other projects)
Context triple: [Parrot virtual machine, supportsLanguage, Python (via Pynie and other projects)]
  • A. Pythion
    Pythion was an ancient city of Perrhaebia in northern Thessaly, Greece, likely known for its regional religious and strategic significance.
  • B. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • C. Python
    Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
  • D. Python
    Python is a classic steel roller coaster in the Efteling theme park in the Netherlands, known for its multiple inversions and status as one of the park’s most iconic thrill rides.
  • E. Python chosen
    Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b48be0481909f4601b732424e5b completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:47 p.m.