Triple

T4353364
Position Surface form Disambiguated ID Type / Status
Subject Semantic Information Processing E98084 entity
Predicate hasPart P35 FINISHED
Object “A Question-Answering System for High School Algebra Word Problems”
“A Question-Answering System for High School Algebra Word Problems” is an early AI research project that automatically interprets and solves algebra word problems in natural language, demonstrating machine understanding and reasoning in mathematics.
E434312 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: “A Question-Answering System for High School Algebra Word Problems” | Statement: [Semantic Information Processing, hasPart, “A Question-Answering System for High School Algebra Word Problems”]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: “A Question-Answering System for High School Algebra Word Problems”
Context triple: [Semantic Information Processing, hasPart, “A Question-Answering System for High School Algebra Word Problems”]
  • A. “A Decision Method for Elementary Algebra and Geometry”
    “A Decision Method for Elementary Algebra and Geometry” is Alfred Tarski’s influential work that presents a procedure for deciding the truth of statements in elementary algebra and geometry, laying foundations for decision theory in mathematical logic.
  • 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. Outside in the Teaching Machine
    Outside in the Teaching Machine is a collection of essays by postcolonial theorist Gayatri Chakravorty Spivak that critiques global capitalism, education, and representation from the perspective of marginalized voices.
  • D. 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.
  • 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: “A Question-Answering System for High School Algebra Word Problems”
Triple: [Semantic Information Processing, hasPart, “A Question-Answering System for High School Algebra Word Problems”]
Generated description
“A Question-Answering System for High School Algebra Word Problems” is an early AI research project that automatically interprets and solves algebra word problems in natural language, demonstrating machine understanding and reasoning in mathematics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: “A Question-Answering System for High School Algebra Word Problems”
Target entity description: “A Question-Answering System for High School Algebra Word Problems” is an early AI research project that automatically interprets and solves algebra word problems in natural language, demonstrating machine understanding and reasoning in mathematics.
  • A. “A Decision Method for Elementary Algebra and Geometry”
    “A Decision Method for Elementary Algebra and Geometry” is Alfred Tarski’s influential work that presents a procedure for deciding the truth of statements in elementary algebra and geometry, laying foundations for decision theory in mathematical logic.
  • 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. Outside in the Teaching Machine
    Outside in the Teaching Machine is a collection of essays by postcolonial theorist Gayatri Chakravorty Spivak that critiques global capitalism, education, and representation from the perspective of marginalized voices.
  • D. 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.
  • 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.