Triple
T2919678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kungsholmen |
E78688
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object |
Lilla Essingen
Lilla Essingen is a small island and residential district in central Stockholm, known for its waterfront apartments and proximity to the city center.
|
E310297
|
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: Lilla Essingen | Statement: [Kungsholmen, hasNeighbourhood, Lilla Essingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilla Essingen Context triple: [Kungsholmen, hasNeighbourhood, Lilla Essingen]
-
A.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
B.
Mönsterås
Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Löttorp
Löttorp is a small village and local service center located on the Baltic Sea island of Öland in southeastern Sweden.
-
E.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
- 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: Lilla Essingen Triple: [Kungsholmen, hasNeighbourhood, Lilla Essingen]
Generated description
Lilla Essingen is a small island and residential district in central Stockholm, known for its waterfront apartments and proximity to the city center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lilla Essingen Target entity description: Lilla Essingen is a small island and residential district in central Stockholm, known for its waterfront apartments and proximity to the city center.
-
A.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
B.
Mönsterås
Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Löttorp
Löttorp is a small village and local service center located on the Baltic Sea island of Öland in southeastern Sweden.
-
E.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a53f8c8190b188d549f1161e84 |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562fc5f081909c9130f71f379a24 |
completed | March 10, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69b06117ba088190886fa464f54525cd |
completed | March 10, 2026, 6:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0628d5f608190b7a13ac2e8b8d721 |
completed | March 10, 2026, 6:27 p.m. |
Created at: March 8, 2026, 2:54 p.m.