Triple
T18266830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuart Russell |
E437504
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Artificial Intelligence: A Modern Approach |
—
|
NE NERFINISHED |
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: Artificial Intelligence: A Modern Approach | Statement: [Stuart Russell, knownFor, Artificial Intelligence: A Modern Approach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Artificial Intelligence: A Modern Approach Context triple: [Stuart Russell, knownFor, Artificial Intelligence: A Modern Approach]
-
A.
Artificial Intelligence: A Modern Approach to Intelligent Systems (various editions of his AI textbook)
chosen
Artificial Intelligence: A Modern Approach to Intelligent Systems is a widely used university-level textbook that systematically introduces the theory, methods, and applications of modern artificial intelligence.
-
B.
Artificial Intelligence (textbook)
Artificial Intelligence is a widely used foundational textbook by Patrick Henry Winston that introduces core concepts, methods, and applications of AI in a clear, structured manner for students and practitioners.
-
C.
The Master Algorithm
The Master Algorithm is a popular science book by Pedro Domingos that explores the unification of different machine learning paradigms into a single, overarching "master" learning algorithm.
-
D.
"Reinforcement Learning: An Introduction"
"Reinforcement Learning: An Introduction" is a foundational textbook that systematically presents the core concepts, algorithms, and theory of reinforcement learning in an accessible and widely used form.
-
E.
Probabilistic Graphical Models: Principles and Techniques
Probabilistic Graphical Models: Principles and Techniques is a foundational textbook that systematically presents the theory, algorithms, and applications of probabilistic graphical models in machine learning and artificial intelligence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7af85c81909859e7247738a535 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.