Triple
T10292197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | thalidomide |
E241389
|
entity |
| Predicate | isUsedToTreat |
P40313
|
FINISHED |
| Object | multiple myeloma |
—
|
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: multiple myeloma | Statement: [thalidomide, isUsedToTreat, multiple myeloma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedToTreat Context triple: [thalidomide, isUsedToTreat, multiple myeloma]
-
A.
usesTreatment
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
-
B.
knownForTreatmentOf
Indicates that an entity is recognized or notable for providing treatment or medical care for a particular condition, disease, or type of patient.
-
C.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
D.
medicinalUse
chosen
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
E.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d35f048190a215493acdf1f718 |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:42 a.m.