Triple
T16649628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lindström |
E404567
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Greta Lindström
Greta Lindström is a Swedish actress known for her roles in early 20th-century Scandinavian cinema.
|
E1226257
|
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: Greta Lindström | Statement: [Lindström, hasNotableBearer, Greta Lindström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greta Lindström Context triple: [Lindström, hasNotableBearer, Greta Lindström]
-
A.
Greta Lovisa Gustafsson
Greta Lovisa Gustafsson, better known as Greta Garbo, was a legendary Swedish-American film actress renowned for her enigmatic screen presence and iconic roles during Hollywood’s silent and early sound eras.
-
B.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
C.
Margareta Wästberg
Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
-
D.
Agneta Andersson
Agneta Andersson is a Swedish sprint canoer and multiple Olympic gold medalist who was one of the sport’s leading competitors in the 1980s and early 1990s.
-
E.
Agneta Eckemyr
Agneta Eckemyr was a Swedish actress and model known for her work in European cinema and appearances in international fashion magazines during the 1970s and 1980s.
- 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: Greta Lindström Triple: [Lindström, hasNotableBearer, Greta Lindström]
Generated description
Greta Lindström is a Swedish actress known for her roles in early 20th-century Scandinavian cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Greta Lindström Target entity description: Greta Lindström is a Swedish actress known for her roles in early 20th-century Scandinavian cinema.
-
A.
Greta Lovisa Gustafsson
Greta Lovisa Gustafsson, better known as Greta Garbo, was a legendary Swedish-American film actress renowned for her enigmatic screen presence and iconic roles during Hollywood’s silent and early sound eras.
-
B.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
C.
Margareta Wästberg
Margareta Wästberg is known as the spouse of Swedish writer and literary figure Per Wästberg.
-
D.
Agneta Andersson
Agneta Andersson is a Swedish sprint canoer and multiple Olympic gold medalist who was one of the sport’s leading competitors in the 1980s and early 1990s.
-
E.
Agneta Eckemyr
Agneta Eckemyr was a Swedish actress and model known for her work in European cinema and appearances in international fashion magazines during the 1970s and 1980s.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad85ec881909dc6a434a363dab1 |
completed | April 18, 2026, 12:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084c2a8448190a9f05bc7e1ce7a05 |
completed | May 10, 2026, 1:14 p.m. |
| NEDg | Description generation | batch_6a008607434481909d41e7b8d6f9a4a3 |
completed | May 10, 2026, 1:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00868e55dc8190bfc7cd1b78ec4d6d |
completed | May 10, 2026, 1:22 p.m. |
Created at: April 10, 2026, 5:18 a.m.