Triple
T3610656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eduard Einstein |
E76476
|
entity |
| Predicate | hasDiagnosis |
P1005
|
FINISHED |
| Object | schizophrenia |
—
|
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: schizophrenia | Statement: [Eduard Einstein, hasDiagnosis, schizophrenia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiagnosis Context triple: [Eduard Einstein, hasDiagnosis, schizophrenia]
-
A.
diagnosedWith
chosen
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
B.
diagnoses
Indicates that a medical professional identifies and determines the nature or cause of a condition, disease, or problem in a patient.
-
C.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
D.
hasPrognosis
Indicates that one entity (typically a medical condition or case) is associated with an expected course or outcome over time, such as likely progression, duration, or chances of recovery.
-
E.
diagnosisYear
Indicates the calendar year in which a diagnosis was made or recorded for an entity.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc22cac3c8190bc5f7c45d31668c1 |
completed | March 8, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.