Triple
T11958225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU Bison |
E284604
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | Yacc |
E956189
|
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: Yacc | Statement: [GNU Bison, influencedBy, Yacc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yacc Context triple: [GNU Bison, influencedBy, Yacc]
-
A.
Yacc
chosen
Yacc is a classic Unix parser generator tool that converts a formal grammar specification into a parser for programming languages and data formats.
-
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.
POSIX Yacc
POSIX Yacc is the standardized version of the classic Unix parser generator specification that many tools, such as GNU Bison, emulate for compatibility in building parsers from context-free grammars.
-
D.
GNU Flex
GNU Flex is a widely used open-source lexical analyzer generator that produces C-based scanners for tokenizing text according to user-defined patterns.
-
E.
javacc
JavaCC is a popular open-source parser generator for Java that allows developers to define grammars and automatically produce parsers.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903681a00819098c2b5260e2ef834 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471c931a88190a9d29262c62b9472 |
completed | May 1, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:45 p.m.