Triple
T10602352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuart K. Card |
E275781
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Card, Moran, and Newell keystroke-level model
The Card, Moran, and Newell keystroke-level model is a predictive human–computer interaction framework that estimates expert user task completion times by decomposing actions into low-level operations like keystrokes, mouse movements, and mental preparation.
|
E874569
|
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: Card, Moran, and Newell keystroke-level model | Statement: [Stuart K. Card, notableWork, Card, Moran, and Newell keystroke-level model]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Card, Moran, and Newell keystroke-level model Context triple: [Stuart K. Card, notableWork, Card, Moran, and Newell keystroke-level model]
-
A.
An interactive activation model of context effects in letter perception
"An interactive activation model of context effects in letter perception" is a seminal cognitive psychology paper that introduced a computational model explaining how letter and word recognition are influenced by both bottom-up sensory input and top-down contextual information.
-
B.
Human Behavior and the Principle of Least Effort
"Human Behavior and the Principle of Least Effort" is a seminal 1949 book by linguist George Kingsley Zipf that proposes people naturally minimize effort in language and behavior, helping explain patterns such as Zipf’s law in word frequencies.
-
C.
Conversational Monitor System (CMS)
Conversational Monitor System (CMS) is an interactive, single-user operating environment and command shell within IBM's VM family, used primarily for program development, text editing, and running applications.
-
D.
The Universal Computer
The Universal Computer is a book by mathematician and logician Martin Davis that traces the history and development of the concept of computation and the universal Turing machine.
-
E.
Unified Theories of Cognition
Unified Theories of Cognition is a comprehensive cognitive science framework proposed by Allen Newell that seeks to explain diverse mental processes—such as problem solving, memory, and learning—within a single, unified theoretical architecture.
- 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: Card, Moran, and Newell keystroke-level model Triple: [Stuart K. Card, notableWork, Card, Moran, and Newell keystroke-level model]
Generated description
The Card, Moran, and Newell keystroke-level model is a predictive human–computer interaction framework that estimates expert user task completion times by decomposing actions into low-level operations like keystrokes, mouse movements, and mental preparation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Card, Moran, and Newell keystroke-level model Target entity description: The Card, Moran, and Newell keystroke-level model is a predictive human–computer interaction framework that estimates expert user task completion times by decomposing actions into low-level operations like keystrokes, mouse movements, and mental preparation.
-
A.
An interactive activation model of context effects in letter perception
"An interactive activation model of context effects in letter perception" is a seminal cognitive psychology paper that introduced a computational model explaining how letter and word recognition are influenced by both bottom-up sensory input and top-down contextual information.
-
B.
Human Behavior and the Principle of Least Effort
"Human Behavior and the Principle of Least Effort" is a seminal 1949 book by linguist George Kingsley Zipf that proposes people naturally minimize effort in language and behavior, helping explain patterns such as Zipf’s law in word frequencies.
-
C.
Conversational Monitor System (CMS)
Conversational Monitor System (CMS) is an interactive, single-user operating environment and command shell within IBM's VM family, used primarily for program development, text editing, and running applications.
-
D.
The Universal Computer
The Universal Computer is a book by mathematician and logician Martin Davis that traces the history and development of the concept of computation and the universal Turing machine.
-
E.
Unified Theories of Cognition
Unified Theories of Cognition is a comprehensive cognitive science framework proposed by Allen Newell that seeks to explain diverse mental processes—such as problem solving, memory, and learning—within a single, unified theoretical architecture.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded61d5c8190b13890c964b59949 |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eaffcd0819098e0a06a731b602f |
completed | April 10, 2026, 8:33 p.m. |
| NEDg | Description generation | batch_69d961aaf71881908289244e0a490492 |
completed | April 10, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9623cf54081908abcdc88e13d5176 |
completed | April 10, 2026, 8:49 p.m. |
Created at: April 8, 2026, 7:31 p.m.