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.