Triple
T35042930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slime Kingdom |
E1011116
|
entity |
| Predicate | hasFictionalCountryType |
P175946
|
FINISHED |
| Object | elemental kingdom |
—
|
LITERAL FINISHED |
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: elemental kingdom | Statement: [Slime Kingdom, hasFictionalCountryType, elemental kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalCountryType Context triple: [Slime Kingdom, hasFictionalCountryType, elemental kingdom]
-
A.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
B.
countryTypeInFiction
chosen
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.).
-
C.
countryOfOriginFictional
Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
-
D.
nationalityOfFictionalSetting
Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
-
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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffb5c373948190a6606e8caa87a384 |
completed | May 9, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ffb261da788190b41399df8ed895e8 |
completed | May 9, 2026, 10:17 p.m. |
Created at: May 3, 2026, 4:01 p.m.