Triple
T35711337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynn Denlon |
E1031866
|
entity |
| Predicate | medicalProcedurePerformedOn |
P2572
|
FINISHED |
| Object | John Kramer |
—
|
NE NERFINISHED |
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: John Kramer | Statement: [Lynn Denlon, medicalProcedurePerformedOn, John Kramer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalProcedurePerformedOn Context triple: [Lynn Denlon, medicalProcedurePerformedOn, John Kramer]
-
A.
operatedOn
chosen
Indicates that one entity has performed a surgical or procedural operation on another entity.
-
B.
hadProcedure
Indicates that a subject underwent or received a specific medical or clinical procedure.
-
C.
examinedIn
Indicates that one entity is analyzed, inspected, or studied within the context, scope, or setting provided by another entity.
-
D.
medicalEvent
Indicates that a specific health-related occurrence or clinical incident has taken place involving one or more entities.
-
E.
operatedOnBody
Indicates that a medical or surgical procedure was performed on a particular body or body part.
- 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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.