Triple
T34975993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krakozhia |
E1008677
|
entity |
| Predicate | politicalSituationInFilm |
P31282
|
FINISHED |
| Object | experiences political turmoil |
—
|
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: experiences political turmoil | Statement: [Krakozhia, politicalSituationInFilm, experiences political turmoil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalSituationInFilm Context triple: [Krakozhia, politicalSituationInFilm, experiences political turmoil]
-
A.
politicalRoleInPlot
Indicates that an entity holds a specific political function, position, or influence within the context of a particular plot or storyline.
-
B.
politicalTheme
chosen
Indicates that something is related to, characterized by, or primarily concerned with politics, governance, or political issues.
-
C.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
D.
politicalLeaderInvolved
Indicates that a political leader is actively involved in, associated with, or plays a significant role in a specified event, action, or situation.
-
E.
politicalPositionDescribed
Indicates that a political role, office, or stance is being characterized or specified in descriptive terms.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: May 3, 2026, 4:01 p.m.