Triple
T33551166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulrika |
E859334
|
entity |
| Predicate | fictionalMigrationDestination |
P174496
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Ulrika, fictionalMigrationDestination, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalMigrationDestination Context triple: [Ulrika, fictionalMigrationDestination, United States]
-
A.
fictionalCitizenship
Indicates that an entity is recognized as a citizen of a fictional or imaginary polity, realm, or jurisdiction.
-
B.
stateOfFictionalResidence
Indicates the state or region in which a fictional character’s residence is located.
-
C.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
D.
immigrationDestinationFor
chosen
Indicates that a location serves as the destination to which an entity immigrates.
-
E.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
- 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_69f3497b2b68819093207971b5e13dc8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: May 1, 2026, 1:39 a.m.