Triple
T34976065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krakozhian |
E1008679
|
entity |
| Predicate | hasAssociatedFictionalNationality |
P15237
|
FINISHED |
| Object | Krakozhian |
—
|
NE NERFINISHED |
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: Krakozhian | Statement: [Krakozhian, hasAssociatedFictionalNationality, Krakozhian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedFictionalNationality Context triple: [Krakozhian, hasAssociatedFictionalNationality, Krakozhian]
-
A.
associatedWithCountryInFiction
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
-
B.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
C.
nationalityInStory
chosen
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
D.
hasEthnicityInFiction
Indicates that a fictional character or entity is portrayed as having a particular ethnicity within a narrative or fictional context.
-
E.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
- 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_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:01 p.m.