Triple
T12553605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mega-City One |
E300158
|
entity |
| Predicate | locatedAlongInFiction |
P47231
|
FINISHED |
| Object | east coast of North America |
—
|
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: east coast of North America | Statement: [Mega-City One, locatedAlongInFiction, east coast of North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedAlongInFiction Context triple: [Mega-City One, locatedAlongInFiction, east coast of North America]
-
A.
locationWithinFiction
Indicates that one fictional location is situated inside or contained within another fictional location.
-
B.
locatedNearFiction
chosen
Indicates that one fictional entity or place is situated close to another within an imagined or narrative context.
-
C.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
-
D.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
E.
locatedInFictionalContext
Indicates that one entity exists or occurs within the setting or universe of a fictional work associated with another entity.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:58 p.m.