Triple
T10610027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gi protein |
E275980
|
entity |
| Predicate | GβγSubunits |
P28620
|
FINISHED |
| Object | regulate ion channels |
—
|
LITERAL FINISHED |
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: regulate ion channels | Statement: [Gi protein, GβγSubunits, regulate ion channels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GβγSubunits Context triple: [Gi protein, GβγSubunits, regulate ion channels]
-
A.
subunitSymbol
Indicates that one entity is the symbolic or abbreviated representation (symbol) of a subunit of another entity.
-
B.
subunitOf
chosen
Indicates that one entity functions as a component or smaller part within the structure or organization of another, larger entity.
-
C.
enzymeType
Indicates the specific class or category of enzyme associated with an entity or reaction.
-
D.
subunitType
Indicates that one entity is a specific kind or classification of subunit within the structure or composition of another entity.
-
E.
substrateAffinity
Indicates the degree to which one entity tends to bind to, interact with, or preferentially act upon a particular substrate.
- F. None of above.
Provenance (3 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_69d6df59468881909b0c67d3f08c4b76 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7a223c8190854409d76368f3e8 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 7:32 p.m.