“Natural Language Input for a Computer Problem-Solving System”
E434311
“Natural Language Input for a Computer Problem-Solving System” is a seminal research paper in artificial intelligence and computational linguistics that explores how computers can understand and process human language to solve problems.
All labels observed (1)
| Label | Occurrences |
|---|---|
| “Natural Language Input for a Computer Problem-Solving System” canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4353363 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “Natural Language Input for a Computer Problem-Solving System” Context triple: [Semantic Information Processing, hasPart, “Natural Language Input for a Computer Problem-Solving System”]
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A.
the Logic Theorist program
The Logic Theorist program was an early artificial intelligence system developed in the 1950s that automatically proved theorems in symbolic logic and is often regarded as the first AI program.
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B.
General Problem Solver
The General Problem Solver is an early artificial intelligence program designed to model and automate human-like problem-solving across a wide range of domains using general search and reasoning strategies.
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C.
The Logic of Computer Programming
The Logic of Computer Programming is a foundational textbook in theoretical computer science that rigorously develops methods for specifying, proving, and reasoning about the correctness of computer programs.
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D.
"Programs with Common Sense"
"Programs with Common Sense" is a seminal 1959 paper by John McCarthy that introduced the idea of using formal logic to represent common-sense knowledge and reasoning in artificial intelligence systems.
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E.
"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence"
"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence" is the seminal 1955 research proposal by John McCarthy and colleagues that launched the field of artificial intelligence by defining its goals and organizing the landmark 1956 Dartmouth conference.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: “Natural Language Input for a Computer Problem-Solving System” Target entity description: “Natural Language Input for a Computer Problem-Solving System” is a seminal research paper in artificial intelligence and computational linguistics that explores how computers can understand and process human language to solve problems.
-
A.
the Logic Theorist program
The Logic Theorist program was an early artificial intelligence system developed in the 1950s that automatically proved theorems in symbolic logic and is often regarded as the first AI program.
-
B.
General Problem Solver
The General Problem Solver is an early artificial intelligence program designed to model and automate human-like problem-solving across a wide range of domains using general search and reasoning strategies.
-
C.
The Logic of Computer Programming
The Logic of Computer Programming is a foundational textbook in theoretical computer science that rigorously develops methods for specifying, proving, and reasoning about the correctness of computer programs.
-
D.
"Programs with Common Sense"
"Programs with Common Sense" is a seminal 1959 paper by John McCarthy that introduced the idea of using formal logic to represent common-sense knowledge and reasoning in artificial intelligence systems.
-
E.
"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence"
"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence" is the seminal 1955 research proposal by John McCarthy and colleagues that launched the field of artificial intelligence by defining its goals and organizing the landmark 1956 Dartmouth conference.
- F. None of above. chosen
Statements (41)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence paper
ⓘ
computational linguistics paper ⓘ research paper ⓘ scientific article ⓘ |
| addresses |
how to connect linguistic structures to actions
ⓘ
how to interpret user queries in natural language ⓘ limitations of rigid command languages ⓘ |
| aim |
to connect linguistic analysis with problem-solving procedures
ⓘ
to enable computers to accept natural language as input ⓘ |
| contribution |
demonstration that computers can use linguistic input to guide problem solving
ⓘ
early framework for natural language interfaces to problem solvers ⓘ integration of language processing with reasoning systems ⓘ |
| describedAs |
early work on natural language interfaces
ⓘ
seminal paper in artificial intelligence ⓘ seminal paper in computational linguistics ⓘ |
| examines |
control of problem-solving by linguistic information
ⓘ
mapping from sentences to internal problem representations ⓘ representation of meaning from natural language ⓘ |
| field |
artificial intelligence
ⓘ
computational linguistics ⓘ natural language processing ⓘ |
| focusesOn |
how computers can understand human language
ⓘ
processing natural language input ⓘ using language understanding to solve problems ⓘ |
| impact |
bridged computational linguistics and problem-solving research
ⓘ
helped establish natural language input as a core AI problem ⓘ |
| influenced |
development of natural language understanding systems
ⓘ
later research on natural language interfaces ⓘ research on integrating NLP with reasoning ⓘ |
| relatedTo |
dialogue systems
ⓘ
early AI problem solvers ⓘ knowledge representation ⓘ natural language question answering ⓘ |
| topic |
computer problem solving
ⓘ
human–computer interaction ⓘ language-based interfaces ⓘ natural language understanding ⓘ |
| usesConcept |
problem representation
ⓘ
search in problem-solving ⓘ semantic interpretation of language ⓘ syntactic analysis of sentences ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: “Natural Language Input for a Computer Problem-Solving System” Description of subject: “Natural Language Input for a Computer Problem-Solving System” is a seminal research paper in artificial intelligence and computational linguistics that explores how computers can understand and process human language to solve problems.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
Semantic Information Processing
→
hasPart
→
“Natural Language Input for a Computer Problem-Solving System”
ⓘ