Triple
T26815942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GABA |
E675120
|
entity |
| Predicate | receptorTypeInteractedWith |
P161501
|
FINISHED |
| Object | ionotropic receptor |
—
|
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: ionotropic receptor | Statement: [GABA, receptorTypeInteractedWith, ionotropic receptor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receptorTypeInteractedWith Context triple: [GABA, receptorTypeInteractedWith, ionotropic receptor]
-
A.
receptor
Indicates that one entity functions as a receptor for another, typically binding or receiving a signal, substance, or stimulus from it.
-
B.
receptorTypeAtEffector
Indicates that a specific type of receptor is present at, or associated with, a particular effector site or effector cell.
-
C.
receptorSystem
Indicates that one entity functions as a receptor system through which another entity receives, processes, or responds to signals or stimuli.
-
D.
targetsReceptor
Indicates that one entity is directed toward, binds to, or is designed to act upon a specific receptor.
-
E.
ligandType
Indicates the specific kind or category of ligand associated with, or acting upon, an entity in the relationship.
- F. None of above. chosen
Provenance (4 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_69eee9b6b28481909332f83eb17e5170 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61a85eee481909550d515a5b8feea |
completed | May 2, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
| PDg | Predicate description generation | batch_69f6142a0b988190b404d078f73c3cb9 |
completed | May 2, 2026, 3:11 p.m. |
Created at: April 27, 2026, 4:52 a.m.