Triple
T32196334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PD-1 |
E822412
|
entity |
| Predicate | clinicalUseContext |
P164050
|
FINISHED |
| Object | treatment of melanoma |
—
|
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: treatment of melanoma | Statement: [PD-1, clinicalUseContext, treatment of melanoma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clinicalUseContext Context triple: [PD-1, clinicalUseContext, treatment of melanoma]
-
A.
clinicalContext
Indicates the medical situation, setting, or circumstances under which a clinical finding, observation, or action occurs.
-
B.
originalUseContext
Indicates the original situation, setting, or context in which something was intended to be used or applied.
-
C.
clinicalSetting
Indicates that an action, observation, or interaction occurs within a healthcare or medical care environment.
-
D.
clinicalApplication
chosen
Indicates that something is used or intended to be used in a practical medical or healthcare setting for diagnosis, treatment, or patient care.
-
E.
clinicalBaseOf
Indicates that one clinical entity serves as the foundational basis or underlying source for another clinical entity (such as a diagnosis, assessment, or decision).
- 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_69f349093174819086e633c190a51aa8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb3795fc8190bfcb00d45aa887a1 |
completed | May 3, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:36 a.m.