Triple
T13327180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edström |
E317469
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Kristina Edström
Kristina Edström is a Swedish chemist and professor renowned for her research on battery technology and energy storage materials.
|
E1034453
|
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: Kristina Edström | Statement: [Edström, hasNotableBearer, Kristina Edström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristina Edström Context triple: [Edström, hasNotableBearer, Kristina Edström]
-
A.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
-
B.
Ellen Lundström
Ellen Lundström was the first wife of renowned Swedish film director Ingmar Bergman, with whom he had several children before their divorce.
-
C.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
D.
Åsa Larsson
Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
-
E.
Martina Lagercrantz
Martina Lagercrantz was the wife of prominent Swedish literary critic and author Olof Lagercrantz.
- 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: Kristina Edström Triple: [Edström, hasNotableBearer, Kristina Edström]
Generated description
Kristina Edström is a Swedish chemist and professor renowned for her research on battery technology and energy storage materials.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kristina Edström Target entity description: Kristina Edström is a Swedish chemist and professor renowned for her research on battery technology and energy storage materials.
-
A.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
-
B.
Ellen Lundström
Ellen Lundström was the first wife of renowned Swedish film director Ingmar Bergman, with whom he had several children before their divorce.
-
C.
Stina Lindgren
Stina Lindgren is known as the spouse of acclaimed Swedish author Torgny Lindgren.
-
D.
Åsa Larsson
Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
-
E.
Martina Lagercrantz
Martina Lagercrantz was the wife of prominent Swedish literary critic and author Olof Lagercrantz.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992d3b0881909732fbb8db98e44c |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f2f69a88190b11e61a922786fc4 |
completed | May 3, 2026, 10:10 a.m. |
| NEDg | Description generation | batch_69f71fe3cda881909916f7aac0664ead |
completed | May 3, 2026, 10:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7208d47388190b1b51f346b0d1423 |
completed | May 3, 2026, 10:16 a.m. |
Created at: April 9, 2026, 9:30 p.m.