Triple
T20996898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cries and Whispers |
E517172
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Siv Lundgren
Siv Lundgren is a film editor best known for her work on Ingmar Bergman’s acclaimed drama "Cries and Whispers."
|
E1466027
|
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: Siv Lundgren | Statement: [Cries and Whispers, editor, Siv Lundgren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siv Lundgren Context triple: [Cries and Whispers, editor, Siv Lundgren]
-
A.
Ellen Lundström
Ellen Lundström was the first wife of renowned Swedish film director Ingmar Bergman, with whom he had several children before their divorce.
-
B.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
C.
Gunnel Lindblom
Gunnel Lindblom was a Swedish actress and director best known for her frequent collaborations with filmmaker Ingmar Bergman in both film and theater.
-
D.
Gunnel Persson
Gunnel Persson is a Swedish figure known primarily as the former spouse of Sweden’s ex-Prime Minister Göran Persson.
-
E.
Ragne Wiklund
Ragne Wiklund is a Norwegian long-distance speed skater who has won world championship titles and represented Norway at major international competitions, including the Winter Olympics.
- 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: Siv Lundgren Triple: [Cries and Whispers, editor, Siv Lundgren]
Generated description
Siv Lundgren is a film editor best known for her work on Ingmar Bergman’s acclaimed drama "Cries and Whispers."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siv Lundgren Target entity description: Siv Lundgren is a film editor best known for her work on Ingmar Bergman’s acclaimed drama "Cries and Whispers."
-
A.
Ellen Lundström
Ellen Lundström was the first wife of renowned Swedish film director Ingmar Bergman, with whom he had several children before their divorce.
-
B.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
C.
Gunnel Lindblom
Gunnel Lindblom was a Swedish actress and director best known for her frequent collaborations with filmmaker Ingmar Bergman in both film and theater.
-
D.
Gunnel Persson
Gunnel Persson is a Swedish figure known primarily as the former spouse of Sweden’s ex-Prime Minister Göran Persson.
-
E.
Ragne Wiklund
Ragne Wiklund is a Norwegian long-distance speed skater who has won world championship titles and represented Norway at major international competitions, including the Winter Olympics.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc21838081909872eed21bc12a08 |
completed | April 21, 2026, 4:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a095a44adc081908734a4fd2ed66092 |
completed | May 17, 2026, 6:03 a.m. |
| NEDg | Description generation | batch_6a095c10ffec8190ac2948155a98127c |
completed | May 17, 2026, 6:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a095ccae2108190b1a679e581d6f61d |
completed | May 17, 2026, 6:14 a.m. |
Created at: April 16, 2026, 1:51 p.m.