Triple
T15460046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nightwatch (1994 film) |
E371873
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Lotte Andersen
Lotte Andersen is a Danish actress known for her roles in Scandinavian film and television.
|
E1158765
|
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: Lotte Andersen | Statement: [Nightwatch (1994 film), hasCastMember, Lotte Andersen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lotte Andersen Context triple: [Nightwatch (1994 film), hasCastMember, Lotte Andersen]
-
A.
Louise Lunde
Louise Lunde is known as the spouse of American character actor Lance Henriksen.
-
B.
Hanne Jacobsen
Hanne Jacobsen is a Danish choreographer and former dancer best known as the longtime wife of actor Mads Mikkelsen.
-
C.
Brigitte Nielsen
Brigitte Nielsen is a Danish actress, model, and television personality known for her roles in 1980s action films and her high-profile marriage to Sylvester Stallone.
-
D.
Christianne Jensen
Christianne Jensen is a vocalist known for her guest appearance on Jon Bellion’s album "Glory Sound Prep."
-
E.
Inge Nissen
Inge Nissen is a former Danish basketball star best known for her standout collegiate career at Old Dominion University and subsequent induction into multiple halls of fame.
- 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: Lotte Andersen Triple: [Nightwatch (1994 film), hasCastMember, Lotte Andersen]
Generated description
Lotte Andersen is a Danish actress known for her roles in Scandinavian film and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lotte Andersen Target entity description: Lotte Andersen is a Danish actress known for her roles in Scandinavian film and television.
-
A.
Louise Lunde
Louise Lunde is known as the spouse of American character actor Lance Henriksen.
-
B.
Hanne Jacobsen
Hanne Jacobsen is a Danish choreographer and former dancer best known as the longtime wife of actor Mads Mikkelsen.
-
C.
Brigitte Nielsen
Brigitte Nielsen is a Danish actress, model, and television personality known for her roles in 1980s action films and her high-profile marriage to Sylvester Stallone.
-
D.
Christianne Jensen
Christianne Jensen is a vocalist known for her guest appearance on Jon Bellion’s album "Glory Sound Prep."
-
E.
Inge Nissen
Inge Nissen is a former Danish basketball star best known for her standout collegiate career at Old Dominion University and subsequent induction into multiple halls of fame.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f17663c8190b995c7c3129c90d6 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cfd76cc8190b3d8148ffe872887 |
completed | May 9, 2026, 12:47 p.m. |
| NEDg | Description generation | batch_69ff2ead88b0819093046c5f0dae8674 |
completed | May 9, 2026, 12:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2f4a404c81909a391d3d2cba1ee8 |
completed | May 9, 2026, 12:57 p.m. |
Created at: April 10, 2026, 3:32 a.m.