Triple
T15311742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dazed and Confused |
E366053
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Sasha Jenson
Sasha Jenson is an American actor best known for his role in the 1993 coming-of-age film "Dazed and Confused."
|
E1150727
|
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: Sasha Jenson | Statement: [Dazed and Confused, castMember, Sasha Jenson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasha Jenson Context triple: [Dazed and Confused, castMember, Sasha Jenson]
-
A.
Jamie Martin
Jamie Martin is a former American football quarterback who played in the NFL during the 1990s and 2000s, primarily as a backup for several teams including the St. Louis Rams.
-
B.
Tyler Johnston
Tyler Johnston is a Canadian actor best known for playing Stewart on the comedy series "Letterkenny."
-
C.
Benay Venuta
Benay Venuta was an American actress, singer, and dancer known for her work in mid-20th-century film, Broadway, and television musicals.
-
D.
Sage Kotsenburg
Sage Kotsenburg is an American snowboarder best known for winning the first-ever Olympic gold medal in men's slopestyle at the 2014 Winter Olympics in Sochi.
-
E.
Jordan Krause
Jordan Krause is a film producer known for working on the documentary "Love, Antosha," which explores the life and legacy of actor Anton Yelchin.
- 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: Sasha Jenson Triple: [Dazed and Confused, castMember, Sasha Jenson]
Generated description
Sasha Jenson is an American actor best known for his role in the 1993 coming-of-age film "Dazed and Confused."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sasha Jenson Target entity description: Sasha Jenson is an American actor best known for his role in the 1993 coming-of-age film "Dazed and Confused."
-
A.
Jamie Martin
Jamie Martin is a former American football quarterback who played in the NFL during the 1990s and 2000s, primarily as a backup for several teams including the St. Louis Rams.
-
B.
Tyler Johnston
Tyler Johnston is a Canadian actor best known for playing Stewart on the comedy series "Letterkenny."
-
C.
Benay Venuta
Benay Venuta was an American actress, singer, and dancer known for her work in mid-20th-century film, Broadway, and television musicals.
-
D.
Sage Kotsenburg
Sage Kotsenburg is an American snowboarder best known for winning the first-ever Olympic gold medal in men's slopestyle at the 2014 Winter Olympics in Sochi.
-
E.
Jordan Krause
Jordan Krause is a film producer known for working on the documentary "Love, Antosha," which explores the life and legacy of actor Anton Yelchin.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd2d5a88190aead748920f93d47 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8a20c1881909b387aed6f532c3d |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fefa339f988190b470e052c853e4f8 |
completed | May 9, 2026, 9:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefac48df08190ad58e9d455546a57 |
completed | May 9, 2026, 9:13 a.m. |
Created at: April 10, 2026, 3:16 a.m.