Triple
T12277619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elf: The Musical |
E292630
|
entity |
| Predicate | lyricsBy |
P1141
|
FINISHED |
| Object | Chad Beguelin |
E419364
|
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: Chad Beguelin | Statement: [Elf: The Musical, lyricsBy, Chad Beguelin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chad Beguelin Context triple: [Elf: The Musical, lyricsBy, Chad Beguelin]
-
A.
Chad Beguelin
chosen
Chad Beguelin is an American playwright and lyricist known for his work on Broadway musicals such as The Wedding Singer, Aladdin, and The Prom.
-
B.
Sam Koppelman
Sam Koppelman is an American writer and political speechwriter known for co-authoring books with figures like Beto O’Rourke and for his work on voting rights and democracy.
-
C.
Greg Yaitanes
Greg Yaitanes is an American television director and producer known for his work on high-profile series such as House of the Dragon and House.
-
D.
Dan Wootton
Dan Wootton is a New Zealand-born British journalist and broadcaster known for his outspoken, often controversial commentary on politics and popular culture.
-
E.
Barron Gaghan
Barron Gaghan is the child of American screenwriter and director Stephen Gaghan, known for films such as "Traffic" and "Syriana."
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cf06cf08190ac8671dd9bbed03d |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e6d72d081908c8697257df712f1 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.