Triple
T11614721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goody Goody |
E275474
|
entity |
| Predicate | hasNotableComposer |
P4321
|
FINISHED |
| Object | Matty Malneck |
E298696
|
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: Matty Malneck | Statement: [Goody Goody, hasNotableComposer, Matty Malneck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matty Malneck Context triple: [Goody Goody, hasNotableComposer, Matty Malneck]
-
A.
Matty Malneck
chosen
Matty Malneck was an American jazz violinist, songwriter, and bandleader known for his work in the swing era and contributions to film and popular music.
-
B.
Ryan Malgarini
Ryan Malgarini is an American actor best known for his childhood roles in early 2000s films and television, including prominent appearances in family comedies.
-
C.
Larry Atamanuik
Larry Atamanuik is a drummer and percussionist best known for his work in Americana and country music, including performances with artists like Emmylou Harris and Alison Krauss.
-
D.
Matt Czuchry
Matt Czuchry is an American actor best known for his roles on the television series "The Good Wife" and "Gilmore Girls."
-
E.
Matt Luber
Matt Luber is a film producer best known for his work on the action-thriller movie "Into the Blue."
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a044a3088190b92f4674c2d0b443 |
completed | April 10, 2026, 7:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1661bb6f48190a5b613ad99154242 |
completed | April 29, 2026, 1:59 a.m. |
Created at: April 8, 2026, 9:38 p.m.