Triple
T20734061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Herek |
E509644
|
entity |
| Predicate | directorOf |
P537
|
FINISHED |
| Object | Critters |
—
|
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: Critters | Statement: [Stephen Herek, directorOf, Critters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Critters Context triple: [Stephen Herek, directorOf, Critters]
-
A.
Kritter
Kritter is a common crocodilian enemy character from the Donkey Kong video game series, serving as one of the primary foot soldiers of the Kremling Krew.
-
B.
Critters Buggin
Critters Buggin is an experimental jazz-fusion and improvisational rock band known for its eclectic, genre-blending sound and innovative live performances.
-
C.
Critter
Critter is a music producer known for working on the album "Neighborhoods."
-
D.
Critter Country
Critter Country is a themed land at Disneyland known for its rustic woodland setting and attractions featuring animal characters.
-
E.
Critters franchise
chosen
The Critters franchise is a series of American horror-comedy films centered on small, carnivorous alien creatures that terrorize humans.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ef3040819085c8056e75571104 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:31 p.m.