Triple
T16406090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eva Bartok |
E398432
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Dag Molin
Dag Molin was the husband of Hungarian-born British actress Eva Bartok, known for her roles in 1950s European and Hollywood cinema.
|
E1222093
|
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: Dag Molin | Statement: [Eva Bartok, spouse, Dag Molin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dag Molin Context triple: [Eva Bartok, spouse, Dag Molin]
-
A.
Ove Molin
Ove Molin is a former Swedish ice hockey forward best known for his long and successful career with Brynäs IF in the Swedish Hockey League.
-
B.
Kåre Hedebrant
Kåre Hedebrant is a Swedish actor best known for his acclaimed childhood performance as the young boy Oskar in the vampire film "Let the Right One In."
-
C.
Bernt Lindström
Bernt Lindström was a Swedish mathematician known for his contributions to combinatorics, particularly in extremal set theory.
-
D.
Anders Gyldenklou
Anders Gyldenklou was a Swedish nobleman and statesman who rose to one of the highest financial and political offices in the Swedish realm.
-
E.
Arvid Engegård
Arvid Engegård is a Norwegian conductor and violinist known for his work with leading Scandinavian orchestras and chamber ensembles.
- 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: Dag Molin Triple: [Eva Bartok, spouse, Dag Molin]
Generated description
Dag Molin was the husband of Hungarian-born British actress Eva Bartok, known for her roles in 1950s European and Hollywood cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dag Molin Target entity description: Dag Molin was the husband of Hungarian-born British actress Eva Bartok, known for her roles in 1950s European and Hollywood cinema.
-
A.
Ove Molin
Ove Molin is a former Swedish ice hockey forward best known for his long and successful career with Brynäs IF in the Swedish Hockey League.
-
B.
Kåre Hedebrant
Kåre Hedebrant is a Swedish actor best known for his acclaimed childhood performance as the young boy Oskar in the vampire film "Let the Right One In."
-
C.
Bernt Lindström
Bernt Lindström was a Swedish mathematician known for his contributions to combinatorics, particularly in extremal set theory.
-
D.
Anders Gyldenklou
Anders Gyldenklou was a Swedish nobleman and statesman who rose to one of the highest financial and political offices in the Swedish realm.
-
E.
Arvid Engegård
Arvid Engegård is a Norwegian conductor and violinist known for his work with leading Scandinavian orchestras and chamber ensembles.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d2b4e48190b7153f198639e9cd |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00758847948190b616cc85e208ee61 |
completed | May 10, 2026, 12:09 p.m. |
| NEDg | Description generation | batch_6a00761b3d148190af6789ae000b8c0b |
completed | May 10, 2026, 12:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0076727d7c81909bde7f01afcd2373 |
completed | May 10, 2026, 12:13 p.m. |
Created at: April 10, 2026, 5:09 a.m.