Triple
T22577946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Quest |
E544465
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Rich Kidd |
—
|
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: Rich Kidd | Statement: [Lord Quest, collaboratedWith, Rich Kidd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rich Kidd Context triple: [Lord Quest, collaboratedWith, Rich Kidd]
-
A.
Rich Kidd
chosen
Rich Kidd is a Canadian hip-hop producer and rapper known for his influential work in Toronto’s rap scene and collaborations with prominent artists.
-
B.
Ed Biddle
Ed Biddle was one of the notorious Biddle brothers, whose dramatic early-20th-century prison escape in Pennsylvania became a sensational and widely publicized criminal episode.
-
C.
Robby Kiger
Robby Kiger is an American former child actor best known for his role in the 1987 cult horror-comedy film "The Monster Squad."
-
D.
Kyle Craig
Kyle Craig is the rookie LAPD officer who partners with a morally ambiguous veteran detective in the television adaptation of "Training Day."
-
E.
Kyle Kelso
Kyle Kelso is a music producer best known for his work on Blondie’s album "Ghosts of Download."
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15feee27c8190b31c923e1f00a363 |
completed | April 29, 2026, 1:33 a.m. |
Created at: April 16, 2026, 8:53 p.m.