Triple
T34747979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manuela Schwesig |
E1001688
|
entity |
| Predicate | hasBeenDiagnosedWith |
P1005
|
FINISHED |
| Object | breast cancer |
—
|
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: breast cancer | Statement: [Manuela Schwesig, hasBeenDiagnosedWith, breast cancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenDiagnosedWith Context triple: [Manuela Schwesig, hasBeenDiagnosedWith, breast cancer]
-
A.
diagnosedWith
chosen
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
B.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
C.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
D.
hasDiagnosticFinding
Indicates that a subject (e.g., a patient, test, or examination) is associated with a specific diagnostic observation, result, or abnormality identified during medical evaluation.
-
E.
hasDiagnosticCriterion
Indicates that a specific diagnostic criterion is used to define, identify, or determine the presence of a particular condition, disorder, or classification.
- 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_69f76db0367081909b57c50a7fb03025 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 3:59 p.m.