Triple
T22177941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition |
E548094
|
entity |
| Predicate | hasRecipient |
P108
|
FINISHED |
| Object | Josh Tenenbaum |
—
|
NE NERFINISHED |
How this triple was built (3 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: Josh Tenenbaum | Statement: [Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition, hasRecipient, Josh Tenenbaum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Josh Tenenbaum Context triple: [Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition, hasRecipient, Josh Tenenbaum]
-
A.
Michael L. Littman
Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
-
B.
Peter Norvig
Peter Norvig is an American computer scientist and AI researcher best known as the co-author of the leading textbook "Artificial Intelligence: A Modern Approach" and as a longtime director of research at Google.
-
C.
Andrea diSessa
Andrea diSessa is an American educational researcher and cognitive scientist known for his work on physics education, computational literacy, and the design of learning environments.
-
D.
Richard Socher
Richard Socher is a prominent computer scientist and entrepreneur known for his influential work in natural language processing and deep learning, including serving as Chief Scientist at Salesforce and founding the AI company You.com.
-
E.
Stephen Tenenbaum
Stephen Tenenbaum is a film producer best known for his frequent collaborations with director Woody Allen on numerous critically acclaimed movies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Josh Tenenbaum Target entity description: Josh Tenenbaum is a cognitive scientist and MIT professor known for his influential work on probabilistic models of human learning, reasoning, and perception.
-
A.
Michael L. Littman
Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
-
B.
Peter Norvig
Peter Norvig is an American computer scientist and AI researcher best known as the co-author of the leading textbook "Artificial Intelligence: A Modern Approach" and as a longtime director of research at Google.
-
C.
Andrea diSessa
Andrea diSessa is an American educational researcher and cognitive scientist known for his work on physics education, computational literacy, and the design of learning environments.
-
D.
Richard Socher
Richard Socher is a prominent computer scientist and entrepreneur known for his influential work in natural language processing and deep learning, including serving as Chief Scientist at Salesforce and founding the AI company You.com.
-
E.
Stephen Tenenbaum
Stephen Tenenbaum is a film producer best known for his frequent collaborations with director Woody Allen on numerous critically acclaimed movies.
- F. None of above. chosen
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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a6dd5a081908035e81c068d8d5a |
completed | April 28, 2026, 9:45 p.m. |
Created at: April 16, 2026, 8:34 p.m.