Triple
T14330644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ada Vilstrup |
E355336
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Vilstrup
Vilstrup is a Danish surname most notably borne by individuals such as Ada Vilstrup.
|
E1093865
|
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: Vilstrup | Statement: [Ada Vilstrup, familyName, Vilstrup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vilstrup Context triple: [Ada Vilstrup, familyName, Vilstrup]
-
A.
Vildbjerg
Vildbjerg is a Danish town that serves as the administrative center of the former Trehøje Municipality in the Central Denmark Region.
-
B.
Knudshoved
Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
-
C.
Egeskov
Egeskov is a village on the island of Funen in Denmark best known for the nearby Renaissance water castle Egeskov Castle, one of Europe’s best-preserved moated castles.
-
D.
Ansnorveldt
Ansnorveldt is a small rural community in King Township, Ontario, known for its agricultural character and surrounding farmland.
-
E.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
- 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: Vilstrup Triple: [Ada Vilstrup, familyName, Vilstrup]
Generated description
Vilstrup is a Danish surname most notably borne by individuals such as Ada Vilstrup.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vilstrup Target entity description: Vilstrup is a Danish surname most notably borne by individuals such as Ada Vilstrup.
-
A.
Vildbjerg
Vildbjerg is a Danish town that serves as the administrative center of the former Trehøje Municipality in the Central Denmark Region.
-
B.
Knudshoved
Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
-
C.
Egeskov
Egeskov is a village on the island of Funen in Denmark best known for the nearby Renaissance water castle Egeskov Castle, one of Europe’s best-preserved moated castles.
-
D.
Ansnorveldt
Ansnorveldt is a small rural community in King Township, Ontario, known for its agricultural character and surrounding farmland.
-
E.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1def0081908f03cda8e84d20c0 |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46943dac819092f5935d9d312949 |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd4811e2808190b559d8348079ae8f |
completed | May 8, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd48d827488190b4a494d4da64ba51 |
completed | May 8, 2026, 2:22 a.m. |
Created at: April 10, 2026, 1:13 a.m.