Triple
T28667069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miskatonic University |
E725611
|
entity |
| Predicate | countryFictionalEquivalent |
P186947
|
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: [Miskatonic University, countryFictionalEquivalent, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryFictionalEquivalent Context triple: [Miskatonic University, countryFictionalEquivalent, United States]
-
A.
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.).
-
B.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
C.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
D.
countryOfFictionalRepresentation
chosen
Indicates that one entity is the country in which another entity (such as a work or character) is fictionally set or represented.
-
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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: April 28, 2026, 5:01 a.m.