Triple
T279968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Servant of the People (TV series) |
E5330
|
entity |
| Predicate | mainCharacterBecomes |
P6579
|
FINISHED |
| Object | President of Ukraine |
—
|
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: President of Ukraine | Statement: [Servant of the People (TV series), mainCharacterBecomes, President of Ukraine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterBecomes Context triple: [Servant of the People (TV series), mainCharacterBecomes, President of Ukraine]
-
A.
characterRoleSwap
Indicates a relationship where two characters exchange or assume each other’s narrative roles or functions within a story or scenario.
-
B.
characterBasedOn
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
C.
became
chosen
Indicates a change of state or status in which one entity transitions into or assumes the role, condition, or identity of another.
-
D.
cameToPowerAfter
Indicates that one entity assumed authority or control following the rule or tenure of another entity.
-
E.
nameChosenToBe
Indicates that an entity has been given or selected to have a particular name.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25def95c48190bb8ab2259f67b583 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b765f488190b2cbe4b45cd42821 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.