Triple
T32816280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Quervain's tenosynovitis |
E839299
|
entity |
| Predicate | typicalTreatment |
P4714
|
FINISHED |
| Object | rest |
—
|
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: rest | Statement: [de Quervain's tenosynovitis, typicalTreatment, rest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTreatment Context triple: [de Quervain's tenosynovitis, typicalTreatment, rest]
-
A.
commonTreatment
Indicates that two or more entities share at least one treatment, therapy, or medical intervention in common.
-
B.
treatmentType
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
-
C.
possibleTreatment
Indicates that one entity can serve as a potential method or option for treating, alleviating, or managing another entity (typically a condition or disease).
-
D.
treatment
chosen
Indicates that one entity is used as a medical or therapeutic intervention to address, manage, or cure a condition affecting another entity.
-
E.
treatmentOf
Indicates a relationship where one entity administers, provides, or is responsible for a therapeutic intervention directed toward another entity (typically a patient or condition).
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:15 a.m.