Triple
T17438345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hey Porsche |
E424072
|
entity |
| Predicate | musicVideoDirector |
P4911
|
FINISHED |
| Object | Ethan Lader |
—
|
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: Ethan Lader | Statement: [Hey Porsche, musicVideoDirector, Ethan Lader]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ethan Lader Context triple: [Hey Porsche, musicVideoDirector, Ethan Lader]
-
A.
Ethan Lader
chosen
Ethan Lader is a music video director known for helming high-profile pop and R&B videos for major artists.
-
B.
Ethan Hendrickson
Ethan Hendrickson is a writer best known for his work on the song "American Boy."
-
C.
Ethan Snyder
Ethan Snyder is a fictional character from the long-running American soap opera "As the World Turns," known as the son of central character Holden Snyder.
-
D.
Ethan Sanderson
Ethan Sanderson is a fictional character from the television sitcom "The Grinder," which centers on the comedic dynamics of a family involved in law and entertainment.
-
E.
Evan Daugherty
Evan Daugherty is an American screenwriter best known for his work on major Hollywood films such as "Snow White and the Huntsman," "Divergent," and "Teenage Mutant Ninja Turtles."
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff584cc81908207c163f19ff972 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 5:46 a.m.