Triple
T14783981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Another 48 Hrs. |
E347462
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ed O’Ross |
E830477
|
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: Ed O’Ross | Statement: [Another 48 Hrs., starring, Ed O’Ross]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed O’Ross Context triple: [Another 48 Hrs., starring, Ed O’Ross]
-
A.
Ed O'Ross
chosen
Ed O'Ross is an American character actor known for his tough-guy roles in film and television, including appearances in movies like Full Metal Jacket, Red Heat, and Dick Tracy.
-
B.
Ian Ross
Ian Ross is the son of English musician, composer, and record producer Atticus Ross.
-
C.
Adrian Ross
Adrian Ross was a prominent British lyricist and writer best known for his work on Edwardian musical comedies and operettas.
-
D.
David Sillar
David Sillar was a Scottish poet, close friend, and contemporary of Robert Burns, known for his role in the Ayrshire literary circle of the late 18th century.
-
E.
Ken McMillan
Ken McMillan is a prominent computer scientist known for his influential work in formal verification and model checking.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9f1c9c8190a8b28ba0ddd3e2e3 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0d02e28081909a11d6e6fdb8d28c |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:31 a.m.