Triple
T32189659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluebell medical clinic |
E822201
|
entity |
| Predicate | hasSuccessorPhysician |
P198630
|
FINISHED |
| Object | Dr. Zoe Hart |
—
|
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: Dr. Zoe Hart | Statement: [Bluebell medical clinic, hasSuccessorPhysician, Dr. Zoe Hart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuccessorPhysician Context triple: [Bluebell medical clinic, hasSuccessorPhysician, Dr. Zoe Hart]
-
A.
hasDoctorActor
Indicates that a doctor participates as an acting agent in the specified event or relationship.
-
B.
hasHealthcareProvider
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
C.
hasSuccessorUsers
Indicates that one user or set of users is followed or replaced by another user or set of users in a sequence or succession.
-
D.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
E.
hasCommitteeSuccessor
Indicates that one committee is the successor or follow-up body to another committee, continuing its role or responsibilities.
- F. None of above. chosen
Provenance (4 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
| PDg | Predicate description generation | batch_69fef8c2cdd881908c6f44e4dfa5ffd0 |
completed | May 9, 2026, 9:05 a.m. |
Created at: May 1, 2026, 12:35 a.m.