Triple
T8656658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torgny Lindgren |
E205435
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
|
E752340
|
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: Stina Lindgren | Statement: [Torgny Lindgren, spouse, Stina Lindgren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stina Lindgren Context triple: [Torgny Lindgren, spouse, Stina Lindgren]
-
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.
Margareta Wästberg
Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
-
C.
Gunnel Persson
Gunnel Persson is a Swedish figure known primarily as the former spouse of Sweden’s ex-Prime Minister Göran Persson.
-
D.
Ylva Johansson
Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
-
E.
Annette Ekblom
Annette Ekblom is an English actress known for her work in television, film, and theatre, including roles in series such as "Brookside" and "The Broker's Man."
- 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: Stina Lindgren Triple: [Torgny Lindgren, spouse, Stina Lindgren]
Generated description
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stina Lindgren Target entity description: Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
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.
Margareta Wästberg
Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
-
C.
Gunnel Persson
Gunnel Persson is a Swedish figure known primarily as the former spouse of Sweden’s ex-Prime Minister Göran Persson.
-
D.
Ylva Johansson
Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
-
E.
Annette Ekblom
Annette Ekblom is an English actress known for her work in television, film, and theatre, including roles in series such as "Brookside" and "The Broker's Man."
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf285de8c081908abca2189f206a40 |
completed | April 3, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_69cf2bcff84881908a7985fdf8189583 |
completed | April 3, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf2ca1ddac8190a36367e6bba8e3c8 |
completed | April 3, 2026, 2:57 a.m. |
Created at: March 30, 2026, 6:30 p.m.