Triple
T18806309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany Boone |
E459882
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Showtime |
—
|
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: Showtime | Statement: [Tiffany Boone, employer, Showtime]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Showtime Context triple: [Tiffany Boone, employer, Showtime]
-
A.
Showtime
chosen
Showtime is an American premium cable and streaming network known for its original, often edgy series, films, and sports programming.
-
B.
Cinemax
Cinemax is an American premium cable and satellite television network known for airing feature films, original series, and late-night programming.
-
C.
HBO
HBO is a premium American television and streaming network known for producing influential, high-quality original series, films, and documentaries such as "The Sopranos," "Game of Thrones," and "Succession."
-
D.
HBO
HBO is the Dutch sector of universities of applied sciences that focuses on professionally oriented higher education and practical training.
-
E.
Epix
Epix was a premium American cable and streaming television network known for airing recent Hollywood films, original series, and specials before being rebranded as MGM+.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d7f8d08190a3e02fab6dc40bb5 |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:53 a.m.