Triple
T15041237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gröna Lund |
E378603
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Grönan
Grönan is the popular colloquial name for Gröna Lund, a historic amusement park located on Djurgården island in Stockholm, Sweden.
|
E1132981
|
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: Grönan | Statement: [Gröna Lund, hasAlternativeName, Grönan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grönan Context triple: [Gröna Lund, hasAlternativeName, Grönan]
-
A.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
-
B.
Farsta
Farsta is a suburban district in southern Stockholm, Sweden, known for its residential areas, shopping center, and metro connections to the city center.
-
C.
Kluuvi
Kluuvi is a central district of Helsinki, Finland, known as the city’s main commercial and business hub.
-
D.
Brangäne
Brangäne is a loyal confidante and maid to Isolde in Richard Wagner’s opera "Tristan und Isolde," known for her protective role and the fateful substitution of a love potion.
-
E.
Särna
Särna is a small locality in northern Dalarna County, Sweden, known for its forested surroundings and outdoor recreation opportunities.
- 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: Grönan Triple: [Gröna Lund, hasAlternativeName, Grönan]
Generated description
Grönan is the popular colloquial name for Gröna Lund, a historic amusement park located on Djurgården island in Stockholm, Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grönan Target entity description: Grönan is the popular colloquial name for Gröna Lund, a historic amusement park located on Djurgården island in Stockholm, Sweden.
-
A.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
-
B.
Farsta
Farsta is a suburban district in southern Stockholm, Sweden, known for its residential areas, shopping center, and metro connections to the city center.
-
C.
Kluuvi
Kluuvi is a central district of Helsinki, Finland, known as the city’s main commercial and business hub.
-
D.
Brangäne
Brangäne is a loyal confidante and maid to Isolde in Richard Wagner’s opera "Tristan und Isolde," known for her protective role and the fateful substitution of a love potion.
-
E.
Särna
Särna is a small locality in northern Dalarna County, Sweden, known for its forested surroundings and outdoor recreation opportunities.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82e79a481908ddb9609af8c4407 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9de388508190bb0ecc04740cbe15 |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9f2b71808190b961193ae1ddebf0 |
completed | May 9, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9fa89bd481909235d2ec377a0d8e |
completed | May 9, 2026, 2:44 a.m. |
Created at: April 10, 2026, 3 a.m.