Triple
T11991822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burn After Reading |
E285423
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Harry Pfarrer
Harry Pfarrer is a womanizing, paranoid U.S. Marshal portrayed by George Clooney in the dark comedy film "Burn After Reading."
|
E1016540
|
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: Harry Pfarrer | Statement: [Burn After Reading, character, Harry Pfarrer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Pfarrer Context triple: [Burn After Reading, character, Harry Pfarrer]
-
A.
John Hufnagel
John Hufnagel is a prominent Canadian Football League coach and executive best known for leading the Calgary Stampeders to multiple Grey Cup championships.
-
B.
Frank Westphal
Frank Westphal was an American bandleader and pianist active in the early 20th-century popular and jazz music scene.
-
C.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
D.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
E.
Erich Rothacker
Erich Rothacker was a German philosopher and cultural theorist known for his work in philosophical anthropology and the humanities, and for supervising Jürgen Habermas’s doctoral studies.
- 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: Harry Pfarrer Triple: [Burn After Reading, character, Harry Pfarrer]
Generated description
Harry Pfarrer is a womanizing, paranoid U.S. Marshal portrayed by George Clooney in the dark comedy film "Burn After Reading."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harry Pfarrer Target entity description: Harry Pfarrer is a womanizing, paranoid U.S. Marshal portrayed by George Clooney in the dark comedy film "Burn After Reading."
-
A.
John Hufnagel
John Hufnagel is a prominent Canadian Football League coach and executive best known for leading the Calgary Stampeders to multiple Grey Cup championships.
-
B.
Frank Westphal
Frank Westphal was an American bandleader and pianist active in the early 20th-century popular and jazz music scene.
-
C.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
D.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
E.
Erich Rothacker
Erich Rothacker was a German philosopher and cultural theorist known for his work in philosophical anthropology and the humanities, and for supervising Jürgen Habermas’s doctoral studies.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b11ac481909866b611380792e7 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0d2818c8190a1bea5f1fc8a9f59 |
completed | May 3, 2026, 3:28 a.m. |
| NEDg | Description generation | batch_69f6c562d10c8190b76dbf50a0101bae |
completed | May 3, 2026, 3:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c635fc888190891a79da9d7984a0 |
completed | May 3, 2026, 3:51 a.m. |
Created at: April 8, 2026, 9:46 p.m.