Triple
T20430078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alkaline Trio |
E501106
|
entity |
| Predicate | hasMusicalArtist |
P9648
|
FINISHED |
| Object | Matt Skiba |
E1214337
|
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: Matt Skiba | Statement: [Alkaline Trio, hasMusicalArtist, Matt Skiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Skiba Context triple: [Alkaline Trio, hasMusicalArtist, Matt Skiba]
-
A.
Matt Skiba
chosen
Matt Skiba is an American musician, singer, and songwriter best known as the frontman of Alkaline Trio and as a former guitarist and vocalist for Blink-182.
-
B.
Jack Skiba
Jack Skiba was the husband of American singer Patti Page, one of the best-selling female vocalists of the 20th century.
-
C.
Matt Graver
Matt Graver is a seasoned and morally ambiguous CIA operative who orchestrates covert operations against Mexican drug cartels in the film "Sicario."
-
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.
Kyle Scheible
Kyle Scheible is the aloof, rebellious musician and love interest in the coming-of-age film "Lady Bird."
- 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67bac39288190b294b291301ac843 |
completed | April 20, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a088b0777788190be9dbb5cb49194ab |
completed | May 16, 2026, 3:19 p.m. |
Created at: April 16, 2026, 11:31 a.m.