Triple
T26813435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aho–Ullman algorithms for parsing |
E672059
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | parsing algorithm family |
C30686
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: parsing algorithm family Context triple: [Aho–Ullman algorithms for parsing, instanceOf, parsing algorithm family]
-
A.
ALGOL family programming language
An ALGOL family programming language is a high-level, block-structured, imperative language descended from the original ALGOL designs, characterized by clear syntax, lexical scoping, and strong influence on later mainstream languages like Pascal, C, and Java.
-
B.
scanner generator
A scanner generator is a tool that automatically produces lexical analyzers (tokenizers) from high-level specifications of token patterns, typically written using regular expressions.
-
C.
lexical analyzer generator
A lexical analyzer generator is a tool that automatically produces a lexer (tokenizer) from a formal specification of a programming language’s lexical structure, such as regular expressions and token definitions.
-
D.
parser generator
chosen
A parser generator is a tool that automatically produces source code for a parser from a formal grammar specification of a language.
-
E.
hierarchy of formal grammars
A hierarchy of formal grammars is an organized classification of grammars into levels based on their generative power and structural constraints, such as the Chomsky hierarchy from regular to recursively enumerable languages.
- F. None of above.
Provenance (1 batch)
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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
Created at: April 27, 2026, 4:30 a.m.