Triple
T1811724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Klee |
E40345
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Lily Stumpf
Lily Stumpf was the wife of Swiss-German painter Paul Klee and a trained pianist who supported and influenced his artistic career.
|
E272581
|
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: Lily Stumpf | Statement: [Paul Klee, spouse, Lily Stumpf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lily Stumpf Context triple: [Paul Klee, spouse, Lily Stumpf]
-
A.
Natalie Schafer
Natalie Schafer was an American actress best known for playing the wealthy and daffy Lovey Howell on the classic television sitcom "Gilligan's Island."
-
B.
Lila Hotz
Lila Hotz was the first wife of American magazine magnate Henry Luce, co-founder of Time Inc.
-
C.
Madeline Neroni
Madeline Neroni is a captivating, manipulative, and physically disabled beauty in Anthony Trollope’s novel "Barchester Towers," known for using her charm and wit to influence the social and romantic intrigues around her.
-
D.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
-
E.
Lily Weinstein
Lily Weinstein is one of the daughters of disgraced Hollywood film producer Harvey Weinstein.
- 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: Lily Stumpf Triple: [Paul Klee, spouse, Lily Stumpf]
Generated description
Lily Stumpf was the wife of Swiss-German painter Paul Klee and a trained pianist who supported and influenced his artistic career.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lily Stumpf Target entity description: Lily Stumpf was the wife of Swiss-German painter Paul Klee and a trained pianist who supported and influenced his artistic career.
-
A.
Natalie Schafer
Natalie Schafer was an American actress best known for playing the wealthy and daffy Lovey Howell on the classic television sitcom "Gilligan's Island."
-
B.
Lila Hotz
Lila Hotz was the first wife of American magazine magnate Henry Luce, co-founder of Time Inc.
-
C.
Madeline Neroni
Madeline Neroni is a captivating, manipulative, and physically disabled beauty in Anthony Trollope’s novel "Barchester Towers," known for using her charm and wit to influence the social and romantic intrigues around her.
-
D.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
-
E.
Lily Weinstein
Lily Weinstein is one of the daughters of disgraced Hollywood film producer Harvey Weinstein.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c64bc08190b993216890752b46 |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f6cb97c8190bf6e8dbdcae3aabd |
completed | March 9, 2026, 7:28 p.m. |
| NEDg | Description generation | batch_69af201e1a748190905bb221fc5dd01e |
completed | March 9, 2026, 7:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af20ad25588190b8e26e82baba731d |
completed | March 9, 2026, 7:34 p.m. |
Created at: March 4, 2026, 7:32 p.m.