Triple
T22198840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juno (2007 film) |
E548619
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Mateo Messina |
—
|
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: Mateo Messina | Statement: [Juno (2007 film), musicBy, Mateo Messina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mateo Messina Context triple: [Juno (2007 film), musicBy, Mateo Messina]
-
A.
Mateo Messina
chosen
Mateo Messina is an American composer best known for his quirky, melodic film scores, including his award-winning work on the movie "Juno."
-
B.
Mateo Santos
Mateo Santos is a fictional character from the soap opera "All My Children," known for his romantic storyline with Hayley Vaughan.
-
C.
Mateo Flores
Mateo Flores was a renowned Guatemalan long-distance runner, best known for winning the 1952 Boston Marathon and becoming a national sports hero.
-
D.
Sebastian Pardo
Sebastian Pardo is a film producer known for his work on the documentary "Love, Antosha," which explores the life and legacy of actor Anton Yelchin.
-
E.
Diego Ongaro
Diego Ongaro is a computer scientist best known as the creator of the Raft consensus algorithm, a widely used protocol for managing replicated logs in distributed systems.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae98808819081582a57bca6312b |
completed | April 28, 2026, 9:47 p.m. |
Created at: April 16, 2026, 8:36 p.m.