Triple
T10548750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honored Artist of the RSFSR |
E248888
|
entity |
| Predicate | successorInRussia |
P94624
|
FINISHED |
| Object | Honored Artist of the Russian Federation |
—
|
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: Honored Artist of the Russian Federation | Statement: [Honored Artist of the RSFSR, successorInRussia, Honored Artist of the Russian Federation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorInRussia Context triple: [Honored Artist of the RSFSR, successorInRussia, Honored Artist of the Russian Federation]
-
A.
successorAsTsaritsa
Indicates that one entity became the next Tsaritsa, directly succeeding another in that role.
-
B.
successorInAustria
Indicates that one entity directly follows another in a succession or sequence specifically within the context of Austria (e.g., in an office, role, or position).
-
C.
successorAsKingOfPoland
Indicates that one person became the next king of Poland following another person’s reign.
-
D.
successorAsEasternRuler
Indicates that one entity became the next ruler of an eastern domain or territory after another entity.
-
E.
tsarRussia
Indicates that the subject is the tsar (monarch) who rules over Russia.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52710869c81909b6db1a190825bad |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:33 p.m.