Triple
T13423583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allsång på Skansen |
E313419
|
entity |
| Predicate | hasHost |
P2592
|
FINISHED |
| Object |
Petra Marklund
Petra Marklund is a Swedish singer and television presenter best known internationally under her stage name September.
|
E1040740
|
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: Petra Marklund | Statement: [Allsång på Skansen, hasHost, Petra Marklund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petra Marklund Context triple: [Allsång på Skansen, hasHost, Petra Marklund]
-
A.
Mina Sundwall
Mina Sundwall is an American actress best known for playing Penny Robinson in the Netflix science fiction series "Lost in Space."
-
B.
Marianne Dahlbäck
Marianne Dahlbäck is a Swedish architect best known for co-designing Stockholm’s Vasa Museum, one of Scandinavia’s most visited cultural landmarks.
-
C.
Pia Lindström
Pia Lindström is a Swedish-American television journalist and critic, best known as the eldest daughter of legendary actress Ingrid Bergman.
-
D.
Anette Qviberg
Anette Qviberg is a Swedish interior designer and fashion stylist best known for her long-term marriage to actor and martial artist Dolph Lundgren.
-
E.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
- 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: Petra Marklund Triple: [Allsång på Skansen, hasHost, Petra Marklund]
Generated description
Petra Marklund is a Swedish singer and television presenter best known internationally under her stage name September.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Petra Marklund Target entity description: Petra Marklund is a Swedish singer and television presenter best known internationally under her stage name September.
-
A.
Mina Sundwall
Mina Sundwall is an American actress best known for playing Penny Robinson in the Netflix science fiction series "Lost in Space."
-
B.
Marianne Dahlbäck
Marianne Dahlbäck is a Swedish architect best known for co-designing Stockholm’s Vasa Museum, one of Scandinavia’s most visited cultural landmarks.
-
C.
Pia Lindström
Pia Lindström is a Swedish-American television journalist and critic, best known as the eldest daughter of legendary actress Ingrid Bergman.
-
D.
Anette Qviberg
Anette Qviberg is a Swedish interior designer and fashion stylist best known for her long-term marriage to actor and martial artist Dolph Lundgren.
-
E.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaecf13748190ae40c7b95164f914 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7398984f48190adaa1963d261d538 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b4052188190bfb583380460adab |
completed | May 3, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73c0e01288190be3e3abc73df7780 |
completed | May 3, 2026, 12:14 p.m. |
Created at: April 9, 2026, 9:39 p.m.