Triple
T7148533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epistle to Dr Arbuthnot |
E166630
|
entity |
| Predicate | addresseeOccupation |
P39104
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [Epistle to Dr Arbuthnot, addresseeOccupation, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addresseeOccupation Context triple: [Epistle to Dr Arbuthnot, addresseeOccupation, physician]
-
A.
recipientOccupation
chosen
Indicates that the object specifies the job, profession, or role held by the recipient in the described relationship or event.
-
B.
addresseeDescription
Indicates that one entity provides a descriptive characterization or identifying information about the addressee of a communication or message.
-
C.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
allegedOccupation
Indicates that one entity is claimed or reported to be the occupation or job role of another entity, without asserting that this claim is necessarily true.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7d6313c8190bdd34e700fc65502 |
completed | March 27, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.