Triple
T13616820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | As Good as It Gets |
E325336
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Frank Sachs
Frank Sachs is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
|
E1250334
|
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: Frank Sachs | Statement: [As Good as It Gets, character, Frank Sachs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Sachs Context triple: [As Good as It Gets, character, Frank Sachs]
-
A.
Paul Schlesinger
Paul Schlesinger is a British television producer known for his work on acclaimed comedy series, including the mockumentary "Twenty Twelve."
-
B.
Arthur Friedheim
Arthur Friedheim was a prominent late 19th- and early 20th-century pianist and conductor, best known as one of Franz Liszt’s leading students and interpreters.
-
C.
Arthur Ornitz
Arthur Ornitz was an American cinematographer known for his work on numerous films from the 1960s through the 1980s.
-
D.
Walter Seltzer
Walter Seltzer was an American film producer known for his work on science fiction and genre films in the mid-20th century.
-
E.
Douglas Shulman
Douglas Shulman is an American public official who served as the head of the U.S. Internal Revenue Service (IRS) during the late 2000s and early 2010s.
- 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: Frank Sachs Triple: [As Good as It Gets, character, Frank Sachs]
Generated description
Frank Sachs is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frank Sachs Target entity description: Frank Sachs is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
-
A.
Paul Schlesinger
Paul Schlesinger is a British television producer known for his work on acclaimed comedy series, including the mockumentary "Twenty Twelve."
-
B.
Arthur Friedheim
Arthur Friedheim was a prominent late 19th- and early 20th-century pianist and conductor, best known as one of Franz Liszt’s leading students and interpreters.
-
C.
Arthur Ornitz
Arthur Ornitz was an American cinematographer known for his work on numerous films from the 1960s through the 1980s.
-
D.
Walter Seltzer
Walter Seltzer was an American film producer known for his work on science fiction and genre films in the mid-20th century.
-
E.
Douglas Shulman
Douglas Shulman is an American public official who served as the head of the U.S. Internal Revenue Service (IRS) during the late 2000s and early 2010s.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0ad0a7c81909c7972187202db96 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139e10e94819092b71606dbe4f5d5 |
completed | May 11, 2026, 2:07 a.m. |
| NEDg | Description generation | batch_6a013ae388548190b09d2c81e1ab0d02 |
completed | May 11, 2026, 2:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a013b4df74c81908b3b99e276531e13 |
completed | May 11, 2026, 2:13 a.m. |
Created at: April 9, 2026, 9:50 p.m.