Triple
T14585919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leroy & Stitch |
E342314
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Michael Tavera |
E966325
|
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: Michael Tavera | Statement: [Leroy & Stitch, composer, Michael Tavera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Tavera Context triple: [Leroy & Stitch, composer, Michael Tavera]
-
A.
Michael Tavera
chosen
Michael Tavera is an American composer best known for his work on animated films and television series.
-
B.
Ryan Agoncillo
Ryan Agoncillo is a Filipino actor, television host, and model best known for his work on popular variety and talk shows in the Philippines.
-
C.
Michael De Guzman
Michael De Guzman is an American screenwriter best known for his work on the film "Jaws: The Revenge" and various television movies and series.
-
D.
Felix Solis
Felix Solis is an American actor and director best known for his intense character roles in television dramas and crime series.
-
E.
Daniel Salazar
Daniel Salazar is a hardened, resourceful former Salvadoran soldier and barber who becomes a key survivor in the television series "Fear the Walking Dead."
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb421bb308190a457425429ef6aa5 |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda9167b888190abb8f301b0c7c55b |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 10, 2026, 1:24 a.m.