Triple
T10917537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riff-Raff |
E257862
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | George Moss |
E894440
|
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: George Moss | Statement: [Riff-Raff, hasCastMember, George Moss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Moss Context triple: [Riff-Raff, hasCastMember, George Moss]
-
A.
George Moss
chosen
George Moss is an actor known for his role in the film "Riff-Raff."
-
B.
Adam Moss
Adam Moss is an American magazine editor best known for transforming New York Magazine into an influential, award-winning publication during his long tenure as editor-in-chief.
-
C.
Kallum Watkins
Kallum Watkins is an English professional rugby league footballer best known for his successful career as a centre for Leeds Rhinos and the England national team.
-
D.
Dominic Lewis
Dominic Lewis is a British-born film and television composer known for scoring a variety of Hollywood projects across action, animation, and comedy.
-
E.
Nathan Kingsbury
Nathan Kingsbury was an American telecommunications executive for AT&T in the early 20th century, known for his role in shaping U.S. telephone regulation and policy.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7707ebdcc8190b42cafe21c667c82 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23bbf70688190be9315a75582dbe2 |
completed | April 17, 2026, 1:55 p.m. |
Created at: April 8, 2026, 9:22 p.m.