Triple

T2176147
Position Surface form Disambiguated ID Type / Status
Subject GPC E48532 entity
Predicate fullName P16 FINISHED
Object GNU Pascal Compiler E8677 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: GNU Pascal Compiler | Statement: [GPC, fullName, GNU Pascal Compiler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GNU Pascal Compiler
Context triple: [GPC, fullName, GNU Pascal Compiler]
  • A. GNU Pascal chosen
    GNU Pascal is a free, open-source Pascal compiler that is part of the GNU project and designed to be compatible with various Pascal standards.
  • B. Free Pascal
    Free Pascal is an open-source, cross-platform Pascal compiler known for its Delphi compatibility and support for a wide range of architectures and operating systems.
  • C. UCSD Pascal
    UCSD Pascal is a variant of the Pascal programming language designed for the UCSD p-System, notable for its portability and use in early microcomputer environments.
  • D. Pascal
    Pascal is a French surname most famously associated with Blaise Pascal, the 17th-century mathematician, physicist, inventor, and philosopher.
  • E. Pascal
    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.
  • 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_69a88aa3faa48190995b233af6525815 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbece30888190936853740ff6cb02 completed March 7, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d9eff988190a02734bd73616cba completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:45 p.m.