Triple
T10765218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niki Taylor |
E253935
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Viggo Komar
Viggo Komar is one of the children of American supermodel Niki Taylor.
|
E888576
|
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: Viggo Komar | Statement: [Niki Taylor, hasChild, Viggo Komar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viggo Komar Context triple: [Niki Taylor, hasChild, Viggo Komar]
-
A.
Johan Rheborg
Johan Rheborg is a Swedish actor and comedian best known as a member of the comedy group Killinggänget and for his roles in acclaimed Swedish films and television series.
-
B.
Gunnar Wejke
Gunnar Wejke was a Swedish architect known for co-designing major public buildings, including the multi-purpose arena Scandinavium in Gothenburg.
-
C.
Kurt Ludvigsen
Kurt Ludvigsen is a cinematographer best known for his work on the romantic drama film "Autumn in New York."
-
D.
Henrik Uldalen
Henrik Uldalen is a contemporary Norwegian figurative painter known for his ethereal, dreamlike portraits that blend realism with surreal and abstract elements.
-
E.
Nicolai Gädda
Nicolai Gädda is a renowned Swedish operatic tenor celebrated for his exceptional vocal technique, linguistic versatility, and extensive international recording and performance career in the mid-20th century.
- 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: Viggo Komar Triple: [Niki Taylor, hasChild, Viggo Komar]
Generated description
Viggo Komar is one of the children of American supermodel Niki Taylor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Viggo Komar Target entity description: Viggo Komar is one of the children of American supermodel Niki Taylor.
-
A.
Johan Rheborg
Johan Rheborg is a Swedish actor and comedian best known as a member of the comedy group Killinggänget and for his roles in acclaimed Swedish films and television series.
-
B.
Gunnar Wejke
Gunnar Wejke was a Swedish architect known for co-designing major public buildings, including the multi-purpose arena Scandinavium in Gothenburg.
-
C.
Kurt Ludvigsen
Kurt Ludvigsen is a cinematographer best known for his work on the romantic drama film "Autumn in New York."
-
D.
Henrik Uldalen
Henrik Uldalen is a contemporary Norwegian figurative painter known for his ethereal, dreamlike portraits that blend realism with surreal and abstract elements.
-
E.
Nicolai Gädda
Nicolai Gädda is a renowned Swedish operatic tenor celebrated for his exceptional vocal technique, linguistic versatility, and extensive international recording and performance career in the mid-20th century.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a5d5248190badfc5a8ab0215d6 |
completed | April 9, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb0b5c9d8819088edb21a35d8b0dc |
completed | April 14, 2026, 9:25 p.m. |
| NEDg | Description generation | batch_69deb3ef9d0c8190816dc99ed102e03d |
completed | April 14, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69deb4e471648190a00f3a921b5fb657 |
completed | April 14, 2026, 9:43 p.m. |
Created at: April 8, 2026, 9:16 p.m.