Triple
T26492749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doppler ultrasound |
E669200
|
entity |
| Predicate | usedToDiagnose |
P52059
|
FINISHED |
| Object | deep vein thrombosis |
—
|
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: deep vein thrombosis | Statement: [Doppler ultrasound, usedToDiagnose, deep vein thrombosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToDiagnose Context triple: [Doppler ultrasound, usedToDiagnose, deep vein thrombosis]
-
A.
diagnosisMethod
chosen
Indicates the method, procedure, or technique used to establish or confirm a diagnosis for a condition or case.
-
B.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
C.
diagnoses
Indicates that a medical professional identifies and determines the nature or cause of a condition, disease, or problem in a patient.
-
D.
usedAsBiomarkerFor
Indicates that one entity serves as a biomarker for another entity, typically signaling the presence, progression, or risk of a specific condition or biological state.
-
E.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:05 a.m.