Triple
T32196275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PD-1 |
E822412
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | immune checkpoint receptor |
C59321
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: immune checkpoint receptor Context triple: [PD-1, instanceOf, immune checkpoint receptor]
-
A.
immune checkpoint receptor
chosen
An immune checkpoint receptor is a cell-surface protein, typically on immune cells like T cells, that modulates immune responses by delivering inhibitory or stimulatory signals upon binding to its ligand, thereby maintaining self-tolerance and preventing overactivation.
-
B.
immune checkpoint ligand
An immune checkpoint ligand is a molecule, typically expressed on the surface of cells, that binds to corresponding immune checkpoint receptors to modulate and often inhibit immune cell activation and maintain immune homeostasis.
-
C.
checkpoint inhibitor
A checkpoint inhibitor is a type of drug that blocks immune checkpoint proteins, thereby enhancing the immune system’s ability to recognize and attack cancer cells.
-
D.
cluster of differentiation antigen
A cluster of differentiation antigen is a cell surface molecule used as a marker to identify and classify leukocyte subsets and other cell types, often serving functional roles in cell signaling and immune responses.
-
E.
adaptive immune cell
An adaptive immune cell is a lymphocyte, such as a B cell or T cell, that specifically recognizes antigens and generates targeted, long-lasting immune responses through clonal expansion and immunological memory.
- F. None of above.
Provenance (1 batch)
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_69f349093174819086e633c190a51aa8 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:36 a.m.