Triple
T17990890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kingdom |
E430365
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object |
Ghita Nørby
Ghita Nørby is a renowned Danish actress celebrated for her extensive film, television, and theater career, making her one of Denmark’s most prominent and respected performers.
|
E1309674
|
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: Ghita Nørby | Statement: [The Kingdom, leadActor, Ghita Nørby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ghita Nørby Context triple: [The Kingdom, leadActor, Ghita Nørby]
-
A.
Hanne Grotjord
Hanne Grotjord is the wife of Norwegian politician and former Prime Minister Thorbjørn Jagland.
-
B.
Louise Lunde
Louise Lunde is known as the spouse of American character actor Lance Henriksen.
-
C.
Ada Vilstrup
Ada Vilstrup was the wife of German-Danish Expressionist painter Emil Nolde and a close companion throughout his artistic career.
-
D.
Sigrid Sundby
Sigrid Sundby is a Norwegian speed skater who competed internationally as a member of Norway's national team.
-
E.
Marianne Ihlen
Marianne Ihlen was a Norwegian woman best known as Leonard Cohen’s muse and former lover, immortalized in several of his songs and writings.
- 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: Ghita Nørby Triple: [The Kingdom, leadActor, Ghita Nørby]
Generated description
Ghita Nørby is a renowned Danish actress celebrated for her extensive film, television, and theater career, making her one of Denmark’s most prominent and respected performers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ghita Nørby Target entity description: Ghita Nørby is a renowned Danish actress celebrated for her extensive film, television, and theater career, making her one of Denmark’s most prominent and respected performers.
-
A.
Hanne Grotjord
Hanne Grotjord is the wife of Norwegian politician and former Prime Minister Thorbjørn Jagland.
-
B.
Louise Lunde
Louise Lunde is known as the spouse of American character actor Lance Henriksen.
-
C.
Ada Vilstrup
Ada Vilstrup was the wife of German-Danish Expressionist painter Emil Nolde and a close companion throughout his artistic career.
-
D.
Sigrid Sundby
Sigrid Sundby is a Norwegian speed skater who competed internationally as a member of Norway's national team.
-
E.
Marianne Ihlen
Marianne Ihlen was a Norwegian woman best known as Leonard Cohen’s muse and former lover, immortalized in several of his songs and writings.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29f127c81908b0c4cb3787e002c |
completed | April 19, 2026, 10:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a038fa4742881908e476000e24079ae |
completed | May 12, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_6a03920ab9ac8190adac3976ffe3bde2 |
completed | May 12, 2026, 8:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0392edfe6c81908082f99ff2e05c0c |
completed | May 12, 2026, 8:51 p.m. |
Created at: April 10, 2026, 10:23 a.m.