Triple
T14440317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristen Nygaard |
E358068
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Nygaard
Nygaard is a Norwegian surname borne by various notable individuals in fields such as computer science, politics, and the arts.
|
E1099056
|
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: Nygaard | Statement: [Kristen Nygaard, familyName, Nygaard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nygaard Context triple: [Kristen Nygaard, familyName, Nygaard]
-
A.
Nylund
Nylund is a Scandinavian-origin surname most widely recognized through the fictional character Rose Nylund from the television series "The Golden Girls."
-
B.
Eidsvold
Eidsvold is a rural town in Queensland, Australia, known historically for cattle grazing and gold mining along the Burnett River.
-
C.
Lilleaker
Lilleaker is a residential neighborhood in western Oslo, Norway, known for its mix of housing, green areas, and proximity to the Lysaker River.
-
D.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
E.
Blakstad
Blakstad is a village in Agder county, Norway, known as the main local hub for services and administration in the surrounding Froland area.
- 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: Nygaard Triple: [Kristen Nygaard, familyName, Nygaard]
Generated description
Nygaard is a Norwegian surname borne by various notable individuals in fields such as computer science, politics, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nygaard Target entity description: Nygaard is a Norwegian surname borne by various notable individuals in fields such as computer science, politics, and the arts.
-
A.
Nylund
Nylund is a Scandinavian-origin surname most widely recognized through the fictional character Rose Nylund from the television series "The Golden Girls."
-
B.
Eidsvold
Eidsvold is a rural town in Queensland, Australia, known historically for cattle grazing and gold mining along the Burnett River.
-
C.
Lilleaker
Lilleaker is a residential neighborhood in western Oslo, Norway, known for its mix of housing, green areas, and proximity to the Lysaker River.
-
D.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
E.
Blakstad
Blakstad is a village in Agder county, Norway, known as the main local hub for services and administration in the surrounding Froland area.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914c1398819090fa2a74d257ba3e |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bda6ee88190aeec77092eb3576a |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5d8c0e4881908dac3fb5a5ac79bc |
completed | May 8, 2026, 3:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5e46c184819092ebb2b5aad28125 |
completed | May 8, 2026, 3:53 a.m. |
Created at: April 10, 2026, 1:18 a.m.