Triple

T4325378
Position Surface form Disambiguated ID Type / Status
Subject Jinja2 E96622 entity
Predicate supportsVersion P203 FINISHED
Object Python 3
Python 3 is a high-level, interpreted programming language known for its clear syntax, extensive standard library, and widespread use in web development, data science, automation, and scripting.
 E3372 NE FINISHED

How this triple was built (4 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 3 | Statement: [Jinja2, supportsVersion, Python 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Python 3
Context triple: [Jinja2, supportsVersion, Python 3]
  • A. Python 3.8
    Python 3.8 is a major release of the Python programming language that introduced several new language features, performance improvements, and standard library enhancements.
  • 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
    Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
  • D. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • E. Python 3.10
    Python 3.10 is a major release of the Python programming language that introduced structural pattern matching and various syntax and performance improvements.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Python 3
Triple: [Jinja2, supportsVersion, Python 3]
Generated description
Python 3 is a high-level, interpreted programming language known for its clear syntax, extensive standard library, and widespread use in web development, data science, automation, and scripting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Python 3
Target entity description: Python 3 is a high-level, interpreted programming language known for its clear syntax, extensive standard library, and widespread use in web development, data science, automation, and scripting.
  • A. Python 3.8
    Python 3.8 is a major release of the Python programming language that introduced several new language features, performance improvements, and standard library enhancements.
  • B. Python chosen
    Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
  • C. Python
    Python is a monstrous serpent or dragon from Greek mythology, best known for being slain by the god Apollo at Delphi.
  • D. Pythonidae
    Pythonidae is a family of nonvenomous constrictor snakes that includes pythons found across Africa, Asia, and Australia.
  • E. Python 3.10
    Python 3.10 is a major release of the Python programming language that introduced structural pattern matching and various syntax and performance improvements.
  • F. None of above.

Provenance (5 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3512ec18481908a7b5c29b3902b53 completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f5c527d481908aa5552838e1f7d1 completed March 14, 2026, 11:56 p.m.
NEDg Description generation batch_69b5f674c94c81908327336dd4380d2e completed March 14, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_69b5f719d008819090a35e3597a0089f completed March 15, 2026, 12:02 a.m.
Created at: March 12, 2026, 11:13 p.m.