Triple

T16907600
Position Surface form Disambiguated ID Type / Status
Subject WEB E424602 entity
Predicate primaryLanguage P238 FINISHED
Object Pascal E1927 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: Pascal | Statement: [WEB, primaryLanguage, Pascal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pascal
Context triple: [WEB, primaryLanguage, Pascal]
  • A. Pascal chosen
    Pascal is a high-level, strongly typed procedural programming language designed by Niklaus Wirth in the late 1960s, widely used for teaching structured programming and data structuring concepts.
  • B. Pascal
    Pascal is a French surname most famously associated with Blaise Pascal, the 17th-century mathematician, physicist, inventor, and philosopher.
  • C. Pascal
    Pascal is the small, expressive chameleon who serves as Rapunzel’s loyal companion and confidant in Disney’s animated film "Tangled."
  • D. Pascal
    Pascal is a Haitian-Canadian professional boxer and former light-heavyweight world champion known for his explosive style and high-profile bouts.
  • E. Turbo Pascal
    Turbo Pascal is a once-popular integrated development environment and compiler for the Pascal programming language, known for its fast compilation speed and influence on early PC software development.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3ca39f9b08190b15106c6caf895ec completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7b98d5c8190b61de47b246549e3 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.