Triple
T35469890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheelsy, South Carolina |
E1025177
|
entity |
| Predicate | hasFictionalEvents |
P97496
|
FINISHED |
| Object | alien meteorite landing |
—
|
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: alien meteorite landing | Statement: [Wheelsy, South Carolina, hasFictionalEvents, alien meteorite landing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalEvents Context triple: [Wheelsy, South Carolina, hasFictionalEvents, alien meteorite landing]
-
A.
hasFictionalEventType
Indicates that something is associated with, characterized by, or classified under a particular type or category of fictional event.
-
B.
associatedWithFictionalEvent
chosen
Indicates that an entity has a connection or involvement with a fictional event, such as being based on, inspired by, or participating in that imagined occurrence.
-
C.
hasFictionalWar
Indicates that there exists a fictional or imagined war involving the related entities.
-
D.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
E.
hasFictionalDepictions
Indicates that an entity is represented or portrayed in one or more fictional works or narratives.
- 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_69ffde9263248190996f970b6cf6e49d |
completed | May 10, 2026, 1:25 a.m. |
| PD | Predicate disambiguation | batch_69ffdd760f1c8190abc6c0c1cd97ba5f |
completed | May 10, 2026, 1:20 a.m. |
Created at: May 3, 2026, 4:04 p.m.