Triple
T23953991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomainia |
E603727
|
entity |
| Predicate | fictionalContinent |
P90336
|
FINISHED |
| Object | Europe |
—
|
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: Europe | Statement: [Tomainia, fictionalContinent, Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalContinent Context triple: [Tomainia, fictionalContinent, Europe]
-
A.
fictionalGeographicRegion
Indicates that a geographic region exists only in fiction or imagination rather than in the real world.
-
B.
belongsToFictionalContinent
chosen
Indicates that something is located on, associated with, or a part of a specific fictional continent within an imagined world.
-
C.
fictionalPlaceType
Indicates that a place is a fictional location and specifies what type or category of fictional place it is.
-
D.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
E.
fictionalSettingRegion
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
- 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_69e2954222288190a7323554d0cca8d7 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d0d558748190a51b5732a3e6713c |
completed | April 29, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:21 p.m.