Triple
T35469882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheelsy, South Carolina |
E1025177
|
entity |
| Predicate | hasFictionalEconomy |
P35913
|
FINISHED |
| Object | small-town businesses |
—
|
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: small-town businesses | Statement: [Wheelsy, South Carolina, hasFictionalEconomy, small-town businesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalEconomy Context triple: [Wheelsy, South Carolina, hasFictionalEconomy, small-town businesses]
-
A.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
B.
hasFictionalEconomicActivity
chosen
Indicates that an entity is involved in an economic activity that exists only in a fictional or imaginary context.
-
C.
hasFictionalDenomination
Indicates that an entity is associated with a made-up or non-real-world unit, title, or currency used in a fictional context.
-
D.
hasFictionalBank
Indicates that an entity is associated with or possesses a bank that exists only in a fictional or imaginary context.
-
E.
hasFictionalWorldType
Indicates that an entity is associated with, set in, or characterized by a particular type or category of fictional world.
- 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_69f76dfa20d0819089585dc2cf653aea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4:04 p.m.