Triple
T15566893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cashback |
E371139
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Lene Bausager
Lene Bausager is a film producer best known for her work on the Academy Award–nominated short film "Cashback."
|
E1166476
|
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: Lene Bausager | Statement: [Cashback, producer, Lene Bausager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lene Bausager Context triple: [Cashback, producer, Lene Bausager]
-
A.
Lene Christensen
Lene Christensen is a Danish professional football goalkeeper known for playing in the Danish national team setup and in top-tier European women’s club football.
-
B.
Lene Børglum
Lene Børglum is a Danish film producer known for her collaborations with director Nicolas Winding Refn on several acclaimed independent films.
-
C.
Lene Andersen
Lene Andersen is a Danish author and futurist known for her work on democracy, ethics, and societal development.
-
D.
Birgitte Hjort Sørensen
Birgitte Hjort Sørensen is a Danish actress known for her roles in the political drama series "Borgen" and various international film and television productions.
-
E.
Vibeke Windeløv
Vibeke Windeløv is a Danish film producer best known for her long-time collaboration with director Lars von Trier on several acclaimed art-house films.
- 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: Lene Bausager Triple: [Cashback, producer, Lene Bausager]
Generated description
Lene Bausager is a film producer best known for her work on the Academy Award–nominated short film "Cashback."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lene Bausager Target entity description: Lene Bausager is a film producer best known for her work on the Academy Award–nominated short film "Cashback."
-
A.
Lene Christensen
Lene Christensen is a Danish professional football goalkeeper known for playing in the Danish national team setup and in top-tier European women’s club football.
-
B.
Lene Børglum
Lene Børglum is a Danish film producer known for her collaborations with director Nicolas Winding Refn on several acclaimed independent films.
-
C.
Lene Andersen
Lene Andersen is a Danish author and futurist known for her work on democracy, ethics, and societal development.
-
D.
Birgitte Hjort Sørensen
Birgitte Hjort Sørensen is a Danish actress known for her roles in the political drama series "Borgen" and various international film and television productions.
-
E.
Vibeke Windeløv
Vibeke Windeløv is a Danish film producer best known for her long-time collaboration with director Lars von Trier on several acclaimed art-house films.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dde90b081908284d9258d4462e3 |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56bf8cac81909886de5b82849cb2 |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff5752f3188190a70713ebbe928dff |
completed | May 9, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff57d92abc81909cb63cfb51741116 |
completed | May 9, 2026, 3:50 p.m. |
Created at: April 10, 2026, 4:10 a.m.