Triple
T37718881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omega Flight |
E939529
|
entity |
| Predicate | fictionalCountryAssociation |
P133191
|
FINISHED |
| Object | Canada |
—
|
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: Canada | Statement: [Omega Flight, fictionalCountryAssociation, Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCountryAssociation Context triple: [Omega Flight, fictionalCountryAssociation, Canada]
-
A.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
B.
associatedWithCountryInFiction
chosen
Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
-
C.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
D.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
E.
countryTypeInFiction
Indicates that a country is classified according to its role or nature within a fictional context (e.g., fictional, real-but-fictionalized, alternate-history, etc.).
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff65987ff88190b09be64f7c0e1da9 |
completed | May 9, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69ff6525b0548190bef7a9f009e00bb8 |
completed | May 9, 2026, 4:47 p.m. |
Created at: May 3, 2026, 4:18 p.m.