Triple
T22202183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | parallel distributed processing |
E548708
|
entity |
| Predicate | fieldOfStudy |
P3
|
FINISHED |
| Object | computational neuroscience |
—
|
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: computational neuroscience | Statement: [parallel distributed processing, fieldOfStudy, computational neuroscience]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: computational neuroscience Context triple: [parallel distributed processing, fieldOfStudy, computational neuroscience]
-
A.
The Computational Brain
The Computational Brain is an influential book that explores how principles of computation and neural networks can explain brain function and cognition.
-
B.
Neural Computation
Neural Computation is a peer-reviewed scientific journal focusing on theoretical and computational aspects of neural systems, machine learning, and artificial intelligence.
-
C.
A Neurocomputational Perspective
A Neurocomputational Perspective is a philosophical and scientific work by Paul Churchland that advances a connectionist, brain-based account of cognition and challenges traditional symbolic and folk-psychological views of the mind.
-
D.
Biophysics of Computation: Information Processing in Single Neurons
Biophysics of Computation: Information Processing in Single Neurons is a seminal book that rigorously explains how individual neurons perform complex information processing using biophysical and computational principles.
-
E.
Simons Collaborations in Neuroscience
Simons Collaborations in Neuroscience is a research initiative that funds and coordinates large-scale, collaborative projects to advance fundamental understanding of brain function and neural circuits.
- 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: computational neuroscience Target entity description: Computational neuroscience is an interdisciplinary field that uses mathematical models, computer simulations, and theoretical analysis to understand the principles and mechanisms underlying nervous system function and cognition.
-
A.
The Computational Brain
The Computational Brain is an influential book that explores how principles of computation and neural networks can explain brain function and cognition.
-
B.
Neural Computation
Neural Computation is a peer-reviewed scientific journal focusing on theoretical and computational aspects of neural systems, machine learning, and artificial intelligence.
-
C.
A Neurocomputational Perspective
A Neurocomputational Perspective is a philosophical and scientific work by Paul Churchland that advances a connectionist, brain-based account of cognition and challenges traditional symbolic and folk-psychological views of the mind.
-
D.
Biophysics of Computation: Information Processing in Single Neurons
Biophysics of Computation: Information Processing in Single Neurons is a seminal book that rigorously explains how individual neurons perform complex information processing using biophysical and computational principles.
-
E.
Simons Collaborations in Neuroscience
Simons Collaborations in Neuroscience is a research initiative that funds and coordinates large-scale, collaborative projects to advance fundamental understanding of brain function and neural circuits.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b24c6fc81909e6ae62564846bd1 |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.