Triple
T42232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe |
E833
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Helsinki
Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
|
E14163
|
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: Helsinki | Statement: [Europe, hasMajorCity, Helsinki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helsinki Context triple: [Europe, hasMajorCity, Helsinki]
-
A.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
B.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
C.
Hamburg
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
D.
Amsterdam
Amsterdam is the largest city in the Netherlands, renowned as a historic commercial and cultural center characterized by its canals, trading heritage, and role as the country’s principal metropolis.
-
E.
Potsdam
Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
- 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: Helsinki Triple: [Europe, hasMajorCity, Helsinki]
Generated description
Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helsinki Target entity description: Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
-
A.
Copenhagen
Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
-
B.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
C.
Hamburg
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
D.
Amsterdam
Amsterdam is the largest city in the Netherlands, renowned as a historic commercial and cultural center characterized by its canals, trading heritage, and role as the country’s principal metropolis.
-
E.
Potsdam
Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ae236548190bd225d125f23e6c7 |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a29e420aa0819085d796612c24bcac |
completed | Feb. 28, 2026, 7:50 a.m. |
| NEDg | Description generation | batch_69a2a0258b4c8190ba2c1263c534754c |
completed | Feb. 28, 2026, 7:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2a0a1298481909760230232c3823d |
completed | Feb. 28, 2026, 8 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.