Triple
T36599633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MS4A1 |
E902882
|
entity |
| Predicate | hasClinicalUse |
P47123
|
FINISHED |
| Object | diagnostic marker for B-cell lymphomas |
—
|
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: diagnostic marker for B-cell lymphomas | Statement: [MS4A1, hasClinicalUse, diagnostic marker for B-cell lymphomas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClinicalUse Context triple: [MS4A1, hasClinicalUse, diagnostic marker for B-cell lymphomas]
-
A.
hasResearchUse
Indicates that an entity is used for, or associated with, conducting research activities or purposes.
-
B.
hasClinicalBase
Indicates that one entity serves as the clinical foundation, setting, or primary site upon which another entity (such as a study, program, or service) is based or conducted.
-
C.
hasEmergencyUse
Indicates that an entity is authorized, designated, or configured for use specifically in emergency situations or conditions.
-
D.
isUsedForPatients
Indicates that something is employed or applied in the care, treatment, or management of patients.
-
E.
hasClinicalSignificance
chosen
Indicates that something (such as a finding, variant, or condition) has a meaningful impact or relevance in a clinical or medical context.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: May 3, 2026, 4:11 p.m.