Triple
T32189637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluebell medical clinic |
E822201
|
entity |
| Predicate | primaryPhysician |
P182017
|
FINISHED |
| Object | Dr. Zoe Hart |
E237847
|
NE 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: Dr. Zoe Hart | Statement: [Bluebell medical clinic, primaryPhysician, Dr. Zoe Hart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPhysician Context triple: [Bluebell medical clinic, primaryPhysician, Dr. Zoe Hart]
-
A.
mainDoctor
chosen
Indicates that one entity serves as the primary or responsible doctor for another entity (such as a patient or medical case).
-
B.
primaryPractitioners
Indicates the entities that are the main or most directly responsible practitioners of a given activity, field, or practice in relation to another entity.
-
C.
primaryPractice
Indicates that one entity is the main or most significant activity, occupation, or method regularly carried out or used by another entity.
-
D.
primaryPatientBase
Indicates that one entity serves as the main or default patient context or reference base for another entity within a medical or clinical setting.
-
E.
medicalPractice
Indicates a relationship where an entity engages in or carries out the professional provision of medical care or services.
- F. None of above.
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_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34665e47f081909e93c04b75d7b7ea |
completed | June 18, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:35 a.m.