Triple
T19648462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Erskine |
E471741
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Casual |
—
|
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: Casual | Statement: [Maya Erskine, appearedIn, Casual]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casual Context triple: [Maya Erskine, appearedIn, Casual]
-
A.
Casual
chosen
Casual is a dark comedy-drama television series that explores the complicated personal lives and relationships of a bachelor, his newly divorced sister, and her teenage daughter living together.
-
B.
Casual
Casual is an American rapper best known as a founding member of the Oakland-based hip hop collective Hieroglyphics.
-
C.
T-casual
T-casual is a popular single-person, multi-trip public transport ticket used across Barcelona’s integrated metro and bus network.
-
D.
Placid Casual
Placid Casual is an independent record label founded by the Welsh band Super Furry Animals to release their own music and that of like-minded artists.
-
E.
Loose
Loose is a surname most notably associated with American composer and arranger William Loose, known for his prolific work in film and television music.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64126cea88190a1a6929f46de4686 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.