Triple

T8414429
Position Surface form Disambiguated ID Type / Status
Subject GNU userland E198698 entity
Predicate includesComponent P1393 FINISHED
Object GNU Flex E284605 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 Flex | Statement: [GNU userland, includesComponent, GNU Flex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GNU Flex
Context triple: [GNU userland, includesComponent, GNU Flex]
  • A. GNU Flex chosen
    GNU Flex is a widely used open-source lexical analyzer generator that produces C-based scanners for tokenizing text according to user-defined patterns.
  • B. GNU Bison
    GNU Bison is a widely used parser generator that converts context-free grammars into C-based parsers, commonly employed in compilers and interpreters within the GNU ecosystem.
  • C. FLEX
    FLEX is a flexible, demand-responsive bus service operated by the North County Transit District in northern San Diego County, California.
  • D. Backus–Naur Form
    Backus–Naur Form is a formal notation used to define the syntax of programming languages and other formal grammars in a precise, structured way.
  • E. Van Wijngaarden grammars
    Van Wijngaarden grammars are a highly expressive formal grammar formalism, introduced for defining complex programming language syntax and semantics, notably used in the specification of ALGOL 68.
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e328cc8190b3b038005d0bb66f completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce032a25ec819094c6346eb2a7f973 completed April 2, 2026, 5:48 a.m.
Created at: March 30, 2026, 6:06 p.m.