Triple
T19862426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dirty Knobs |
E477297
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Matt Laug |
—
|
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: Matt Laug | Statement: [The Dirty Knobs, hasMember, Matt Laug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Laug Context triple: [The Dirty Knobs, hasMember, Matt Laug]
-
A.
Matt Laug
chosen
Matt Laug is an American rock drummer best known for his session and touring work with artists like Alanis Morissette and Alice Cooper.
-
B.
Matt Walst
Matt Walst is a Canadian rock singer best known as the lead vocalist of the band Three Days Grace.
-
C.
Matt Oberg
Matt Oberg is an American actor and comedian known for his work in television comedies and voice acting roles.
-
D.
Matt Luber
Matt Luber is a film producer best known for his work on the action-thriller movie "Into the Blue."
-
E.
Matt Harpring
Matt Harpring is a former American professional basketball player and standout small forward best known for his collegiate career at Georgia Tech and his NBA tenure with teams including the Utah Jazz.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589b3cbc8190afe847e83f04c45b |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.