Triple
T15008843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuber |
E377781
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Stu Prasad
Stu Prasad is the mild-mannered, risk-averse rideshare driver protagonist of the action-comedy film "Stuber."
|
E1132204
|
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: Stu Prasad | Statement: [Stuber, mainCharacter, Stu Prasad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stu Prasad Context triple: [Stuber, mainCharacter, Stu Prasad]
-
A.
Ashwanth Ashokkumar
Ashwanth Ashokkumar is an Indian child actor best known for his acclaimed performance in the Tamil film "Super Deluxe."
-
B.
Sanjay Reddy
Sanjay Reddy is an Indian economist known for his work in development economics, poverty measurement, and global justice.
-
C.
Raj Subramaniam
Raj Subramaniam is the President and Chief Executive Officer of FedEx Corporation, a leading global logistics and delivery services company.
-
D.
Srinu Vaitla
Srinu Vaitla is an Indian film director best known for his work in Telugu cinema, particularly for directing successful commercial comedies and action entertainers.
-
E.
Keith Shankar
Keith Shankar is a central character in the dark comedy TV series "Black Monday," which satirically explores the events surrounding the 1987 stock market crash.
- 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: Stu Prasad Triple: [Stuber, mainCharacter, Stu Prasad]
Generated description
Stu Prasad is the mild-mannered, risk-averse rideshare driver protagonist of the action-comedy film "Stuber."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stu Prasad Target entity description: Stu Prasad is the mild-mannered, risk-averse rideshare driver protagonist of the action-comedy film "Stuber."
-
A.
Ashwanth Ashokkumar
Ashwanth Ashokkumar is an Indian child actor best known for his acclaimed performance in the Tamil film "Super Deluxe."
-
B.
Sanjay Reddy
Sanjay Reddy is an Indian economist known for his work in development economics, poverty measurement, and global justice.
-
C.
Raj Subramaniam
Raj Subramaniam is the President and Chief Executive Officer of FedEx Corporation, a leading global logistics and delivery services company.
-
D.
Srinu Vaitla
Srinu Vaitla is an Indian film director best known for his work in Telugu cinema, particularly for directing successful commercial comedies and action entertainers.
-
E.
Keith Shankar
Keith Shankar is a central character in the dark comedy TV series "Black Monday," which satirically explores the events surrounding the 1987 stock market crash.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe96a52bb08190961e3f18d751fe2a |
completed | May 9, 2026, 2:06 a.m. |
| NEDg | Description generation | batch_69fe98bf505c819089740180a763db34 |
completed | May 9, 2026, 2:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9aab47888190812ff9732380e124 |
completed | May 9, 2026, 2:23 a.m. |
Created at: April 10, 2026, 2:55 a.m.