Triple
T16649660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lindström |
E404567
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sanna Lindström
Sanna Lindström is a notable individual who carries the Swedish surname Lindström, recognized for her prominence in association with that name.
|
E1227879
|
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: Sanna Lindström | Statement: [Lindström, hasNotableBearer, Sanna Lindström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanna Lindström Context triple: [Lindström, hasNotableBearer, Sanna Lindström]
-
A.
Ulla-Britt Söderlund
Ulla-Britt Söderlund was a Swedish costume designer best known for her work on historically detailed and influential films of the 1960s and 1970s, including the Oscar-winning costumes for "Barry Lyndon."
-
B.
Sari Lindblom
Sari Lindblom is a Finnish academic and higher education leader who serves as the rector of the University of Helsinki.
-
C.
Anne Leppälä-Nilsson
Anne Leppälä-Nilsson is a Finnish politician who has served as the mayor of the city of Hämeenlinna.
-
D.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
E.
Greta Lindström
Greta Lindström is a Swedish actress known for her roles in early 20th-century Scandinavian cinema.
- 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: Sanna Lindström Triple: [Lindström, hasNotableBearer, Sanna Lindström]
Generated description
Sanna Lindström is a notable individual who carries the Swedish surname Lindström, recognized for her prominence in association with that name.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sanna Lindström Target entity description: Sanna Lindström is a notable individual who carries the Swedish surname Lindström, recognized for her prominence in association with that name.
-
A.
Ulla-Britt Söderlund
Ulla-Britt Söderlund was a Swedish costume designer best known for her work on historically detailed and influential films of the 1960s and 1970s, including the Oscar-winning costumes for "Barry Lyndon."
-
B.
Sari Lindblom
Sari Lindblom is a Finnish academic and higher education leader who serves as the rector of the University of Helsinki.
-
C.
Anne Leppälä-Nilsson
Anne Leppälä-Nilsson is a Finnish politician who has served as the mayor of the city of Hämeenlinna.
-
D.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
E.
Greta Lindström
Greta Lindström is a Swedish actress known for her roles in early 20th-century Scandinavian cinema.
- 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_6a008a2f1da48190a1a01dbe25f8f0e9 |
completed | May 10, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_6a008b5135788190af6cfca6cb333d26 |
completed | May 10, 2026, 1:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008bee78248190b920d780bcbd3032 |
completed | May 10, 2026, 1:45 p.m. |
Created at: April 10, 2026, 5:18 a.m.