Triple
T3717864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Hodgkin |
E81573
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Hodgkin–Huxley model
The Hodgkin–Huxley model is a mathematical description of how action potentials in neurons are initiated and propagated through voltage-gated ion channels in the cell membrane.
|
E381979
|
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: Hodgkin–Huxley model | Statement: [Alan Hodgkin, knownFor, Hodgkin–Huxley model]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hodgkin–Huxley model Context triple: [Alan Hodgkin, knownFor, Hodgkin–Huxley model]
-
A.
all-or-none principle in nerve excitation
The all-or-none principle in nerve excitation is the physiological rule that a nerve fiber, once stimulated beyond a certain threshold, responds with a full, uniform action potential rather than a graded response.
-
B.
SNN
SNN is the National Rail station code assigned to Swinton railway station in South Yorkshire, England.
-
C.
Ian Hodgkin
Ian Hodgkin is a person notable enough to be recognized as a bearer of the Hodgkin surname.
-
D.
Hebbian learning
Hebbian learning is a neurobiological and computational learning principle often summarized as "cells that fire together wire together," where the connection between neurons is strengthened when they are activated simultaneously.
-
E.
Hopfield networks
Hopfield networks are recurrent artificial neural networks that serve as content-addressable memory systems, storing patterns as stable states and retrieving them through dynamics that minimize an energy function.
- 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: Hodgkin–Huxley model Triple: [Alan Hodgkin, knownFor, Hodgkin–Huxley model]
Generated description
The Hodgkin–Huxley model is a mathematical description of how action potentials in neurons are initiated and propagated through voltage-gated ion channels in the cell membrane.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hodgkin–Huxley model Target entity description: The Hodgkin–Huxley model is a mathematical description of how action potentials in neurons are initiated and propagated through voltage-gated ion channels in the cell membrane.
-
A.
all-or-none principle in nerve excitation
The all-or-none principle in nerve excitation is the physiological rule that a nerve fiber, once stimulated beyond a certain threshold, responds with a full, uniform action potential rather than a graded response.
-
B.
SNN
SNN is the National Rail station code assigned to Swinton railway station in South Yorkshire, England.
-
C.
Ian Hodgkin
Ian Hodgkin is a person notable enough to be recognized as a bearer of the Hodgkin surname.
-
D.
Hebbian learning
Hebbian learning is a neurobiological and computational learning principle often summarized as "cells that fire together wire together," where the connection between neurons is strengthened when they are activated simultaneously.
-
E.
Hopfield networks
Hopfield networks are recurrent artificial neural networks that serve as content-addressable memory systems, storing patterns as stable states and retrieving them through dynamics that minimize an energy function.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca984844819087a2f6b20d2f19e7 |
completed | March 8, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce1260948190b4707337e9427c2c |
completed | March 14, 2026, 2:55 a.m. |
| NEDg | Description generation | batch_69b4cf799ae88190bbf821f4c4500031 |
completed | March 14, 2026, 3:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4d0057fe8819092a40732324f88c9 |
completed | March 14, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:33 p.m.