Triple
T19754617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Railsea |
E474470
|
entity |
| Predicate | coverArtist |
P184
|
FINISHED |
| Object | Shane Rebenschied |
—
|
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: Shane Rebenschied | Statement: [Railsea, coverArtist, Shane Rebenschied]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shane Rebenschied Context triple: [Railsea, coverArtist, Shane Rebenschied]
-
A.
Shane Rebenschied
chosen
Shane Rebenschied is an illustrator and graphic artist known for creating book and publication cover art.
-
B.
Kevin Reher
Kevin Reher is an American film producer best known for his work on Pixar animated features, including the Cars franchise.
-
C.
Craig Heisinger
Craig Heisinger is a Canadian ice hockey executive best known for his long-time leadership role with the Manitoba Moose organization.
-
D.
Brian Schmetzer
Brian Schmetzer is an American soccer coach best known for leading Seattle Sounders FC to multiple MLS Cup titles and establishing the club as a perennial league contender.
-
E.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6529dada081909c5b4d65247c6032 |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:48 p.m.