Triple
T34091938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimulti |
E874319
|
entity |
| Predicate | receptorBinding |
P142668
|
FINISHED |
| Object | CB1 receptor antagonist |
—
|
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: CB1 receptor antagonist | Statement: [Zimulti, receptorBinding, CB1 receptor antagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receptorBinding Context triple: [Zimulti, receptorBinding, CB1 receptor antagonist]
-
A.
receptorTypeInteractedWith
Indicates that one entity has interacted with, bound to, or otherwise engaged a specific type of receptor.
-
B.
receptor
Indicates that one entity functions as a receptor for another, typically binding or receiving a signal, substance, or stimulus from it.
-
C.
receptorSubtype
Indicates that one receptor is a specific subtype or variant within the broader class defined by another receptor.
-
D.
receptorSystem
Indicates that one entity functions as a receptor system through which another entity receives, processes, or responds to signals or stimuli.
-
E.
targetsReceptor
chosen
Indicates that one entity is directed toward, binds to, or is designed to act upon a specific receptor.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:52 a.m.