Triple
T12782808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lost in America |
E305548
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Michael Greene
Michael Greene is an actor best known for his role in the 1985 comedy film "Lost in America."
|
E1007331
|
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: Michael Greene | Statement: [Lost in America, starring, Michael Greene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Greene Context triple: [Lost in America, starring, Michael Greene]
-
A.
Scott Greer
Scott Greer is an American political commentator and writer known for his nationalist and right-wing perspectives, particularly through his work at outlets like The Daily Caller.
-
B.
Philip Dunne
Philip Dunne was an American screenwriter, director, and producer best known for his work on classic Hollywood films from the 1930s through the 1960s.
-
C.
Jack Briggs
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
-
D.
Michael Greenwood
Michael Greenwood is a member of the Greenwood family, known primarily as a son of British politician Hamar Greenwood, 1st Viscount Greenwood.
-
E.
Eric Brooks
Eric Brooks is the human-vampire hybrid vampire hunter better known as the Marvel Comics character Blade.
- 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: Michael Greene Triple: [Lost in America, starring, Michael Greene]
Generated description
Michael Greene is an actor best known for his role in the 1985 comedy film "Lost in America."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Greene Target entity description: Michael Greene is an actor best known for his role in the 1985 comedy film "Lost in America."
-
A.
Scott Greer
Scott Greer is an American political commentator and writer known for his nationalist and right-wing perspectives, particularly through his work at outlets like The Daily Caller.
-
B.
Philip Dunne
Philip Dunne was an American screenwriter, director, and producer best known for his work on classic Hollywood films from the 1930s through the 1960s.
-
C.
Jack Briggs
Jack Briggs was an American actor best known for his marriage to Hollywood star Ginger Rogers.
-
D.
Michael Greenwood
Michael Greenwood is a member of the Greenwood family, known primarily as a son of British politician Hamar Greenwood, 1st Viscount Greenwood.
-
E.
Eric Brooks
Eric Brooks is the human-vampire hybrid vampire hunter better known as the Marvel Comics character Blade.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5b52048190b279b7ad066efe9f |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b925b3c81909f5e604c0f457645 |
completed | May 3, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69f69c46a6208190a113aefbce1bbaac |
completed | May 3, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69cead6d881909765424b5391a613 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 9, 2026, 5:29 p.m.