Triple
T4709958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Into the Blue |
E104483
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Tyson Beckford |
E253937
|
NE FINISHED |
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: Tyson Beckford | Statement: [Into the Blue, starring, Tyson Beckford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyson Beckford Context triple: [Into the Blue, starring, Tyson Beckford]
-
A.
Tyson Beckford
chosen
Tyson Beckford is an American model and actor best known as one of the most prominent male supermodels of the 1990s and a longtime face of Ralph Lauren.
-
B.
Kei Kamara
Kei Kamara is a Sierra Leonean professional footballer and prolific striker known for being one of Major League Soccer’s all-time leading goal scorers.
-
C.
Henry Adebonojo
Henry Adebonojo is a cinematographer best known for his work on the acclaimed documentary film "I Am Not Your Negro."
-
D.
Akeem Browder
Akeem Browder is an American activist and advocate for criminal justice reform, known for his work following the wrongful incarceration and tragic death of his younger brother, Kalief Browder.
-
E.
Cuonzo Martin
Cuonzo Martin is an American college basketball coach known for leading multiple Division I programs, including Missouri, Tennessee, and California.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63ee712c81908da60aa0df58efe0 |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1078784c81908e9a3fd0b168cadc |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:17 p.m.