Triple
T17974332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stacey Weitzman |
E449426
|
entity |
| Predicate | hasUndergoneMedicalTreatmentFor |
P95317
|
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: [Stacey Weitzman, hasUndergoneMedicalTreatmentFor, breast cancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergoneMedicalTreatmentFor Context triple: [Stacey Weitzman, hasUndergoneMedicalTreatmentFor, breast cancer]
-
A.
hasReceivedTreatmentFor
chosen
Indicates that an entity has undergone or been given a treatment in relation to a specified condition, issue, or problem.
-
B.
hadProcedure
Indicates that a subject underwent or received a specific medical or clinical procedure.
-
C.
hasSurgery
Indicates that a surgical procedure is performed on or undergone by an entity.
-
D.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fe24808190baa11739f4d1095f |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.