Triple
T9839745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scary Movie 2 |
E239190
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Greg Grabianski
Greg Grabianski is a screenwriter best known for his work on the parody horror-comedy film "Scary Movie 2."
|
E825468
|
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: Greg Grabianski | Statement: [Scary Movie 2, writer, Greg Grabianski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Grabianski Context triple: [Scary Movie 2, writer, Greg Grabianski]
-
A.
Adam Haslett
Adam Haslett is an American author and journalist known for his critically acclaimed fiction exploring themes of mental illness, family, and contemporary politics.
-
B.
Michael Grant
Michael Grant is a relatively private individual best known in public records as the former husband of Athena Grant.
-
C.
Dan Erickson
Dan Erickson is a television writer and producer best known for creating the acclaimed sci-fi thriller series "Severance."
-
D.
Adam Johnson
Adam Johnson is a Pulitzer Prize–winning American author best known for his novel "The Orphan Master's Son," which explores life in North Korea.
-
E.
Aaron Guzikowski
Aaron Guzikowski is an American screenwriter best known for writing the acclaimed thriller film "Prisoners" and creating the science fiction series "Raised by Wolves."
- 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: Greg Grabianski Triple: [Scary Movie 2, writer, Greg Grabianski]
Generated description
Greg Grabianski is a screenwriter best known for his work on the parody horror-comedy film "Scary Movie 2."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Greg Grabianski Target entity description: Greg Grabianski is a screenwriter best known for his work on the parody horror-comedy film "Scary Movie 2."
-
A.
Adam Haslett
Adam Haslett is an American author and journalist known for his critically acclaimed fiction exploring themes of mental illness, family, and contemporary politics.
-
B.
Michael Grant
Michael Grant is a relatively private individual best known in public records as the former husband of Athena Grant.
-
C.
Dan Erickson
Dan Erickson is a television writer and producer best known for creating the acclaimed sci-fi thriller series "Severance."
-
D.
Adam Johnson
Adam Johnson is a Pulitzer Prize–winning American author best known for his novel "The Orphan Master's Son," which explores life in North Korea.
-
E.
Aaron Guzikowski
Aaron Guzikowski is an American screenwriter best known for writing the acclaimed thriller film "Prisoners" and creating the science fiction series "Raised by Wolves."
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb34b045481908f89abd576aab497 |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5d5484c8190a78ccd0e9816ba51 |
completed | April 5, 2026, 3:24 a.m. |
| NEDg | Description generation | batch_69d1d9c17a308190818dd21e7e53af9d |
completed | April 5, 2026, 3:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1da4ee3588190aa46d2eeffd0eabd |
completed | April 5, 2026, 3:43 a.m. |
Created at: March 30, 2026, 8:33 p.m.