Triple
T31732353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Top 10 |
E809893
|
entity |
| Predicate | fictionalCityType |
P71480
|
FINISHED |
| Object | city where nearly everyone has superpowers |
—
|
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: city where nearly everyone has superpowers | Statement: [Top 10, fictionalCityType, city where nearly everyone has superpowers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCityType Context triple: [Top 10, fictionalCityType, city where nearly everyone has superpowers]
-
A.
fictionalCitySetting
Indicates that a narrative, event, or work is set in a city that is imaginary or does not exist in the real world.
-
B.
fictionalCapital
Indicates that a location serves as the capital city within a fictional or imaginary political or geographic entity.
-
C.
fictionalPlaceType
chosen
Indicates that a place is a fictional location and specifies what type or category of fictional place it is.
-
D.
hasFictionalTownType
Indicates that a fictional town is classified as being of a particular type or category.
-
E.
fictionalCityContext
Indicates that the relationship or information is situated within, or pertains specifically to, the setting of a fictional city.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd7e364a648190a1e9e1d9fc76e99e |
completed | May 8, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69fd7bb547608190a3b04dddbca6b8bc |
completed | May 8, 2026, 5:59 a.m. |
Created at: April 30, 2026, 11:22 p.m.