Triple
T12986729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ctesias of Cnidus |
E321786
|
entity |
| Predicate | professionAtCourt |
P45619
|
FINISHED |
| Object | royal 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: royal physician | Statement: [Ctesias of Cnidus, professionAtCourt, royal physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionAtCourt Context triple: [Ctesias of Cnidus, professionAtCourt, royal physician]
-
A.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
B.
legalProfessionIncludes
Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
-
C.
defendantProfession
Indicates the professional occupation or job role held by the defendant in a legal case.
-
D.
jurorProfession
Indicates that an individual serves in the professional role or capacity of a juror in a legal proceeding.
-
E.
roleAtCourt
chosen
Indicates the specific position, function, or status an entity holds within a court or courtly setting.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:40 p.m.