Triple
T9474461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Well |
E228477
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object |
Ann Kron
Ann Kron is a central character in the 2017 film "Well," around whom the story’s main events and emotional developments revolve.
|
E803217
|
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: Ann Kron | Statement: [Well, hasMainCharacter, Ann Kron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ann Kron Context triple: [Well, hasMainCharacter, Ann Kron]
-
A.
Ann Wagner
Ann Wagner is the mother of American actress and businesswoman Priscilla Presley.
-
B.
Anna Kuhn
Anna Kuhn was the mother of Nobel Prize–winning theoretical physicist Hans Bethe.
-
C.
Kate Soffel
Kate Soffel is the real-life warden’s wife whose illicit romance with a condemned prisoner inspired the 1984 film "Mrs. Soffel."
-
D.
Lisa Bluder
Lisa Bluder is a longtime head coach of the University of Iowa women's basketball team, known for leading the Hawkeyes to national prominence behind star players like Caitlin Clark.
-
E.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
- 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: Ann Kron Triple: [Well, hasMainCharacter, Ann Kron]
Generated description
Ann Kron is a central character in the 2017 film "Well," around whom the story’s main events and emotional developments revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ann Kron Target entity description: Ann Kron is a central character in the 2017 film "Well," around whom the story’s main events and emotional developments revolve.
-
A.
Ann Wagner
Ann Wagner is the mother of American actress and businesswoman Priscilla Presley.
-
B.
Anna Kuhn
Anna Kuhn was the mother of Nobel Prize–winning theoretical physicist Hans Bethe.
-
C.
Kate Soffel
Kate Soffel is the real-life warden’s wife whose illicit romance with a condemned prisoner inspired the 1984 film "Mrs. Soffel."
-
D.
Lisa Bluder
Lisa Bluder is a longtime head coach of the University of Iowa women's basketball team, known for leading the Hawkeyes to national prominence behind star players like Caitlin Clark.
-
E.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ff23aec8190b5341eb9bd816a43 |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139f261248190b8e3238f7618191d |
completed | April 4, 2026, 4:18 p.m. |
| NEDg | Description generation | batch_69d13a8e79b081908d5b4dce125df678 |
completed | April 4, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d13b1d2cb481908cdcbeb1a6c81794 |
completed | April 4, 2026, 4:23 p.m. |
Created at: March 30, 2026, 7:54 p.m.