Triple
T3305339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray Costello |
E69433
|
entity |
| Predicate | typeOfDoctor |
P12790
|
FINISHED |
| Object | medical doctor |
—
|
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: medical doctor | Statement: [Murray Costello, typeOfDoctor, medical doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfDoctor Context triple: [Murray Costello, typeOfDoctor, medical doctor]
-
A.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
B.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
-
C.
practiceType
chosen
Indicates the specific kind or category of practice associated with an entity or activity.
-
D.
typeOfScientist
Indicates that one entity is a scientist and the other specifies the kind or specialization of that scientist.
-
E.
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.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0c9470881908c36c1984fdbb67b |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada42625308190be257f16a623a410 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.