Triple
T1987355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hangover |
E43171
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Scott Moore
Scott Moore is an American screenwriter best known for co-writing the hit comedy film "The Hangover."
|
E226507
|
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: Scott Moore | Statement: [The Hangover, writer, Scott Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Moore Context triple: [The Hangover, writer, Scott Moore]
-
A.
Nick Moore
Nick Moore is a British film editor best known for his work on popular films such as "Love Actually."
-
B.
Richard Moore
Richard Moore was an early 17th-century English colonial administrator who became the inaugural governor of Bermuda, helping to establish the island’s first formal government.
-
C.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
D.
Tim McClelland
Tim McClelland is a former Major League Baseball umpire known for his long tenure, distinctive strike zone, and involvement in several high-profile postseason games.
-
E.
William Moore
William Moore was an early settler and landowner after whom the city of Raymore, Missouri, was named.
- 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: Scott Moore Triple: [The Hangover, writer, Scott Moore]
Generated description
Scott Moore is an American screenwriter best known for co-writing the hit comedy film "The Hangover."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scott Moore Target entity description: Scott Moore is an American screenwriter best known for co-writing the hit comedy film "The Hangover."
-
A.
Nick Moore
Nick Moore is a British film editor best known for his work on popular films such as "Love Actually."
-
B.
Richard Moore
Richard Moore was an early 17th-century English colonial administrator who became the inaugural governor of Bermuda, helping to establish the island’s first formal government.
-
C.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
D.
Tim McClelland
Tim McClelland is a former Major League Baseball umpire known for his long tenure, distinctive strike zone, and involvement in several high-profile postseason games.
-
E.
William Moore
William Moore was an early settler and landowner after whom the city of Raymore, Missouri, was named.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb840a5708190a9b64564b855fb22 |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ad53ccc8190b0e0f44cfddfe9a4 |
completed | March 8, 2026, 11:48 p.m. |
| NEDg | Description generation | batch_69ae0b49abfc81908876ea54c7b7dcc2 |
completed | March 8, 2026, 11:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0d1bb5c881908c27bdd359e78773 |
completed | March 8, 2026, 11:58 p.m. |
Created at: March 4, 2026, 7:37 p.m.