Triple
T14561277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Garden |
E341669
|
entity |
| Predicate | hasNearbyAttraction |
P2064
|
FINISHED |
| Object |
Nyboder
Nyboder is a historic district in Copenhagen known for its distinctive 17th-century yellow terraced houses originally built to house Royal Danish Navy personnel.
|
E1106662
|
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: Nyboder | Statement: [King’s Garden, hasNearbyAttraction, Nyboder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyboder Context triple: [King’s Garden, hasNearbyAttraction, Nyboder]
-
A.
Nannfeldt
Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
-
B.
Norén
Norén is a Swedish surname, notably borne by actress Noomi Rapace before she adopted her stage name.
-
C.
Mörby
Mörby is a locality in the Stockholm area of Sweden served by a station on the Roslagsbanan narrow-gauge railway line.
-
D.
Edsbyn
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
-
E.
Norsborg
Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
- 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: Nyboder Triple: [King’s Garden, hasNearbyAttraction, Nyboder]
Generated description
Nyboder is a historic district in Copenhagen known for its distinctive 17th-century yellow terraced houses originally built to house Royal Danish Navy personnel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nyboder Target entity description: Nyboder is a historic district in Copenhagen known for its distinctive 17th-century yellow terraced houses originally built to house Royal Danish Navy personnel.
-
A.
Nannfeldt
Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
-
B.
Norén
Norén is a Swedish surname, notably borne by actress Noomi Rapace before she adopted her stage name.
-
C.
Mörby
Mörby is a locality in the Stockholm area of Sweden served by a station on the Roslagsbanan narrow-gauge railway line.
-
D.
Edsbyn
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
-
E.
Norsborg
Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb389d0f48190a1d9d69456d1cbe1 |
completed | April 14, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ac294748190a4bfeed8c5fd9e94 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8c3678048190a23b509e963c1ade |
completed | May 8, 2026, 7:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8d609684819090a9c3f2304f4a6a |
completed | May 8, 2026, 7:14 a.m. |
Created at: April 10, 2026, 1:23 a.m.