Triple
T17748683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Lo |
E443053
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mr. Nice Guy |
—
|
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: Mr. Nice Guy | Statement: [Ken Lo, notableWork, Mr. Nice Guy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Nice Guy Context triple: [Ken Lo, notableWork, Mr. Nice Guy]
-
A.
Nice Guy
"Nice Guy" is a track by Eminem from his 2018 album *Kamikaze*, known for its aggressive style and introspective lyrics.
-
B.
The Good Guy
"The Good Guy" is a 2009 romantic dramedy film about the complexities of modern relationships and Wall Street culture, starring Trini Alvarado among its cast.
-
C.
Good Guy
"Good Guy" is a song featured on the album "Kamikaze" by American rapper Eminem.
-
D.
Mr. Nice
chosen
Mr. Nice is a 2010 biographical crime film in which Rhys Ifans portrays real-life Welsh drug smuggler Howard Marks.
-
E.
Perfect Man
The Perfect Man is a central Sufi metaphysical concept describing the fully realized human who perfectly reflects divine attributes and serves as the spiritual axis of creation.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad46a50819089c87f74efe3c7ca |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:10 a.m.