Triple
T13616821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | As Good as It Gets |
E325336
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Beverly Connelly
Beverly Connelly is a supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
|
E1168574
|
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: Beverly Connelly | Statement: [As Good as It Gets, character, Beverly Connelly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beverly Connelly Context triple: [As Good as It Gets, character, Beverly Connelly]
-
A.
Carol Connelly
Carol Connelly is a compassionate single mother and waitress in the film "As Good as It Gets," whose relationship with a misanthropic writer drives much of the story’s emotional core.
-
B.
Beverly Morrow
Beverly Morrow is known as a close friend and companion of Bill Sackter, the intellectually disabled man whose life story inspired the film "Bill."
-
C.
Beverly Kelly
Beverly Kelly is best known as the wife of American actor James Coburn.
-
D.
Beverly Penn
Beverly Penn is a young heiress in the fantasy romance film "Winter's Tale" whose tragic, otherworldly love story drives the movie's central themes of destiny and miracles.
-
E.
Beverly Todd
Beverly Todd is an American actress known for her work in film, television, and theater, including a notable role in the comedy-drama "The Bucket List."
- 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: Beverly Connelly Triple: [As Good as It Gets, character, Beverly Connelly]
Generated description
Beverly Connelly is a 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: Beverly Connelly Target entity description: Beverly Connelly is a supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
-
A.
Carol Connelly
Carol Connelly is a compassionate single mother and waitress in the film "As Good as It Gets," whose relationship with a misanthropic writer drives much of the story’s emotional core.
-
B.
Beverly Morrow
Beverly Morrow is known as a close friend and companion of Bill Sackter, the intellectually disabled man whose life story inspired the film "Bill."
-
C.
Beverly Kelly
Beverly Kelly is best known as the wife of American actor James Coburn.
-
D.
Beverly Penn
Beverly Penn is a young heiress in the fantasy romance film "Winter's Tale" whose tragic, otherworldly love story drives the movie's central themes of destiny and miracles.
-
E.
Beverly Todd
Beverly Todd is an American actress known for her work in film, television, and theater, including a notable role in the comedy-drama "The Bucket List."
- 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_69ff5f1f80648190a4a0e8260ac95194 |
completed | May 9, 2026, 4:21 p.m. |
| NEDg | Description generation | batch_69ff5fea7cb48190a1acb9201a12fa32 |
completed | May 9, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff62e84bec81908a4885bf7f8f3749 |
completed | May 9, 2026, 4:38 p.m. |
Created at: April 9, 2026, 9:50 p.m.