Triple

T4353363
Position Surface form Disambiguated ID Type / Status
Subject Semantic Information Processing E98084 entity
Predicate hasPart P35 FINISHED
Object “Natural Language Input for a Computer Problem-Solving System”
“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.
E434311 NE FINISHED

How this triple was built (4 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: “Natural Language Input for a Computer Problem-Solving System” | Statement: [Semantic Information Processing, hasPart, “Natural Language Input for a Computer Problem-Solving System”]
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”]
  • 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
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: “Natural Language Input for a Computer Problem-Solving System”
Triple: [Semantic Information Processing, hasPart, “Natural Language Input for a Computer Problem-Solving System”]
Generated 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.
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

Provenance (5 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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c281688190aef717c4ecce8107 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbb32eb081908dbaa8cc14882fe0 completed March 14, 2026, 10:05 p.m.
NEDg Description generation batch_69b5df8336e881908c875b8411c2fe4d completed March 14, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_69b5e0ded0288190b615364e9ae10821 completed March 14, 2026, 10:27 p.m.
Created at: March 12, 2026, 11:15 p.m.