Triple
T18334576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kindergarten Cop 2 |
E439236
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object |
Don Michael Paul
Don Michael Paul is an American filmmaker and former actor known for directing numerous direct-to-video action and genre films.
|
E1318983
|
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: Don Michael Paul | Statement: [Kindergarten Cop 2, director, Don Michael Paul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Michael Paul Context triple: [Kindergarten Cop 2, director, Don Michael Paul]
-
A.
David Michael Frank
David Michael Frank is an American composer best known for his work on film and television scores.
-
B.
Jeff Michael
Jeff Michael is a composer best known for his work on the science fiction television series "Star Trek: The Animated Series."
-
C.
Robert Michael Morris
Robert Michael Morris was an American actor best known for his comedic role as the eccentric acting teacher Mickey Deane on the HBO series "The Comeback."
-
D.
Michael Petulla
Michael Petulla is a musician best known as a member of the English indie folk band Noah and the Whale.
-
E.
Michael Bruxner
Michael Bruxner was an Australian politician and long-serving leader of the Country Party in New South Wales, noted for his influence on rural policy and infrastructure development.
- 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: Don Michael Paul Triple: [Kindergarten Cop 2, director, Don Michael Paul]
Generated description
Don Michael Paul is an American filmmaker and former actor known for directing numerous direct-to-video action and genre films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Don Michael Paul Target entity description: Don Michael Paul is an American filmmaker and former actor known for directing numerous direct-to-video action and genre films.
-
A.
David Michael Frank
David Michael Frank is an American composer best known for his work on film and television scores.
-
B.
Jeff Michael
Jeff Michael is a composer best known for his work on the science fiction television series "Star Trek: The Animated Series."
-
C.
Robert Michael Morris
Robert Michael Morris was an American actor best known for his comedic role as the eccentric acting teacher Mickey Deane on the HBO series "The Comeback."
-
D.
Michael Petulla
Michael Petulla is a musician best known as a member of the English indie folk band Noah and the Whale.
-
E.
Michael Bruxner
Michael Bruxner was an Australian politician and long-serving leader of the Country Party in New South Wales, noted for his influence on rural policy and infrastructure development.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecc91148190aa820fcd466009ce |
completed | April 19, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03c4d2db288190b5832978f53265ca |
completed | May 13, 2026, 12:24 a.m. |
| NEDg | Description generation | batch_6a03c8b9d06c8190af9e9121246b7e6f |
completed | May 13, 2026, 12:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03c989741c81908f2a50b571a8c475 |
completed | May 13, 2026, 12:44 a.m. |
Created at: April 10, 2026, 10:36 a.m.