Triple
T15636494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother’s Day (2010 film) |
E375958
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Brian Witten
Brian Witten is a film producer known for his work on genre and mainstream movies, including the 2010 horror film "Mother’s Day."
|
E1171907
|
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: Brian Witten | Statement: [Mother’s Day (2010 film), producer, Brian Witten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Witten Context triple: [Mother’s Day (2010 film), producer, Brian Witten]
-
A.
Rob Scott
Rob Scott is a New Zealand local government leader serving as the mayor of Southland District.
-
B.
Brad Wyman
Brad Wyman is a film producer best known for his work on independent movies such as "Monster" and other genre-driven projects.
-
C.
Ben Boulware
Ben Boulware is an American former linebacker best known for starring on Clemson University's national championship-winning football team and earning All-American honors.
-
D.
Brian Kessler
Brian Kessler is a young writer and true-crime enthusiast who embarks on a cross-country road trip to research serial killers in the film "Kalifornia."
-
E.
Joe Wredden
Joe Wredden is an actor known for his role in the 2013 television miniseries "The Bible."
- 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: Brian Witten Triple: [Mother’s Day (2010 film), producer, Brian Witten]
Generated description
Brian Witten is a film producer known for his work on genre and mainstream movies, including the 2010 horror film "Mother’s Day."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brian Witten Target entity description: Brian Witten is a film producer known for his work on genre and mainstream movies, including the 2010 horror film "Mother’s Day."
-
A.
Rob Scott
Rob Scott is a New Zealand local government leader serving as the mayor of Southland District.
-
B.
Brad Wyman
Brad Wyman is a film producer best known for his work on independent movies such as "Monster" and other genre-driven projects.
-
C.
Ben Boulware
Ben Boulware is an American former linebacker best known for starring on Clemson University's national championship-winning football team and earning All-American honors.
-
D.
Brian Kessler
Brian Kessler is a young writer and true-crime enthusiast who embarks on a cross-country road trip to research serial killers in the film "Kalifornia."
-
E.
Joe Wredden
Joe Wredden is an actor known for his role in the 2013 television miniseries "The Bible."
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb8b4c48190b80fea6877483089 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7568028481908caa1e49541bbcf1 |
completed | May 9, 2026, 5:56 p.m. |
| NEDg | Description generation | batch_69ff763d40348190bf102da746420390 |
completed | May 9, 2026, 6 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff76ec45948190bee47609c0d2fd10 |
completed | May 9, 2026, 6:03 p.m. |
Created at: April 10, 2026, 4:14 a.m.