Triple
T13008613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snoopy, Come Home |
E322350
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Bill Melendez |
E736338
|
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: Bill Melendez | Statement: [Snoopy, Come Home, producer, Bill Melendez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Melendez Context triple: [Snoopy, Come Home, producer, Bill Melendez]
-
A.
Bill Melendez
chosen
Bill Melendez was a Mexican-American animator, director, and producer best known for bringing the Peanuts comic strip to life in animated television specials and films.
-
B.
Waddy Wachtel
Waddy Wachtel is an American guitarist, songwriter, and record producer best known for his prolific session work and collaborations with major rock and pop artists since the 1970s.
-
C.
Mark Wolper
Mark Wolper is a television and film producer best known for his work on various entertainment and game shows, including serving as an executive producer on "Funny You Should Ask."
-
D.
Hal Jacobs
Hal Jacobs is one of the children of Irwin M. Jacobs, the American engineer and co-founder of Qualcomm.
-
E.
Norman I. Badler
Norman I. Badler is an American computer scientist known for his pioneering work in computer graphics, human modeling, and animation, and for his long tenure as a professor at the University of Pennsylvania.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9cf0108190b02f498c6ccc91f8 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbc77f308190b3b47f7a092db434 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:48 p.m.