Triple
T3308915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Valiant |
E69521
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | “A Theory of the Learnable” |
E345811
|
NE FINISHED |
How this triple was built (2 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 Theory of the Learnable” | Statement: [Leslie Valiant, notableWork, “A Theory of the Learnable”]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “A Theory of the Learnable” Context triple: [Leslie Valiant, notableWork, “A Theory of the Learnable”]
-
A.
Probably Approximately Correct learning (PAC learning)
chosen
Probably Approximately Correct (PAC) learning is a foundational framework in computational learning theory that formalizes what it means for an algorithm to efficiently learn a concept from examples with high probability and small error.
-
B.
“Probably Approximately Correct” (book)
“Probably Approximately Correct” is a 2013 book by computer scientist Leslie Valiant that explores how ideas from computational learning theory can explain intelligence, evolution, and the way we understand the world.
-
C.
P, NP, and NP-Completeness: The Basics of Complexity Theory
"P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
-
D.
"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.
-
E.
Lifelong Learning Machines program
The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0e9f33c81909cff835a83e0a657 |
completed | March 8, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a73c1c8819082e522221a8b2a54 |
completed | March 12, 2026, 7:56 p.m. |
Created at: March 8, 2026, 3:11 p.m.