Triple
T15227289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nilsson |
E363907
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Emma Nilsson
Emma Nilsson is a person bearing the Swedish surname Nilsson, which is common in Scandinavian countries.
|
E1145925
|
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: Emma Nilsson | Statement: [Nilsson, hasNotableBearer, Emma Nilsson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Nilsson Context triple: [Nilsson, hasNotableBearer, Emma Nilsson]
-
A.
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.
-
B.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
-
C.
Greta Lundgren
Greta Lundgren is a daughter of Swedish actor and martial artist Dolph Lundgren.
-
D.
Nilla Svensdotter
Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
-
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: Emma Nilsson Triple: [Nilsson, hasNotableBearer, Emma Nilsson]
Generated description
Emma Nilsson is a person bearing the Swedish surname Nilsson, which is common in Scandinavian countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Emma Nilsson Target entity description: Emma Nilsson is a person bearing the Swedish surname Nilsson, which is common in Scandinavian countries.
-
A.
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.
-
B.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
-
C.
Greta Lundgren
Greta Lundgren is a daughter of Swedish actor and martial artist Dolph Lundgren.
-
D.
Nilla Svensdotter
Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
-
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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078bb32881909927561c6c072546 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5edca5c8190827788324a9e886d |
completed | May 9, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69fee6706764819099ad22a6289ac465 |
completed | May 9, 2026, 7:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fee706214081909468535055497b8f |
completed | May 9, 2026, 7:49 a.m. |
Created at: April 10, 2026, 3:12 a.m.