Triple
T22945111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Ruritania |
E569844
|
entity |
| Predicate | settingCountryFictional |
P20932
|
FINISHED |
| Object | Ruritania |
—
|
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: Ruritania | Statement: [Princess of Ruritania, settingCountryFictional, Ruritania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingCountryFictional Context triple: [Princess of Ruritania, settingCountryFictional, Ruritania]
-
A.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
B.
countryOfOriginFictional
Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
-
C.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
D.
locatedInFictionalCountry
chosen
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
E.
associatedWithCountryInFiction
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819c696c8190977bd2bca01509bc |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.