Triple
T1108651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbie (2023 film) |
E25542
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Nick Houy
Nick Houy is a film editor known for his work on major feature films, including the 2023 movie "Barbie."
|
E161011
|
NE FINISHED |
How this triple was built (4 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: Nick Houy | Statement: [Barbie (2023 film), editedBy, Nick Houy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Houy Context triple: [Barbie (2023 film), editedBy, Nick Houy]
-
A.
Ken Howery
Ken Howery is an American entrepreneur, venture capitalist, and co-founder of PayPal who later served as a partner at Founders Fund and as U.S. Ambassador to Sweden.
-
B.
Jeff Henley
Jeff Henley is an American business executive best known for his long tenure as Oracle Corporation’s chief financial officer and later chairman of the board.
-
C.
Kevin Yagher
Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
-
D.
John Toon
John Toon is a cinematographer known for his work on the film "Sunshine Cleaning."
-
E.
John Sarrao
John Sarrao is an American physicist and scientific leader known for his work in condensed matter physics and for directing major U.S. research institutions, including the SLAC National Accelerator Laboratory.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nick Houy Triple: [Barbie (2023 film), editedBy, Nick Houy]
Generated description
Nick Houy is a film editor known for his work on major feature films, including the 2023 movie "Barbie."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nick Houy Target entity description: Nick Houy is a film editor known for his work on major feature films, including the 2023 movie "Barbie."
-
A.
Ken Howery
Ken Howery is an American entrepreneur, venture capitalist, and co-founder of PayPal who later served as a partner at Founders Fund and as U.S. Ambassador to Sweden.
-
B.
Jeff Henley
Jeff Henley is an American business executive best known for his long tenure as Oracle Corporation’s chief financial officer and later chairman of the board.
-
C.
Kevin Yagher
Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
-
D.
John Toon
John Toon is a cinematographer known for his work on the film "Sunshine Cleaning."
-
E.
John Sarrao
John Sarrao is an American physicist and scientific leader known for his work in condensed matter physics and for directing major U.S. research institutions, including the SLAC National Accelerator Laboratory.
- F. None of above. chosen
Provenance (5 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e6134481909f348986a25f65c6 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ace54f52988190b25c35271721c3ee |
completed | March 8, 2026, 2:56 a.m. |
| NEDg | Description generation | batch_69ace5db553c8190b0d09462411f3dcf |
completed | March 8, 2026, 2:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ace647c04881908ab550505110c29b |
completed | March 8, 2026, 3 a.m. |
Created at: March 1, 2026, 7:43 p.m.