Triple
T15040390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Söderort |
E378584
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Hägersten-Liljeholmen
Hägersten-Liljeholmen is a suburban district and borough in the southern part of Stockholm, Sweden, known for its mix of residential areas, parks, and waterfront along Lake Mälaren.
|
E1132930
|
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: Hägersten-Liljeholmen | Statement: [Söderort, hasPart, Hägersten-Liljeholmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hägersten-Liljeholmen Context triple: [Söderort, hasPart, Hägersten-Liljeholmen]
-
A.
Lill-Jansskogen
Lill-Jansskogen is a large urban forest and recreational park area in Stockholm, Sweden, popular for walking, running, and outdoor activities.
-
B.
Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
-
C.
Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
-
D.
Lindhagen
Lindhagen is a Swedish surname most notably associated with the politician and social reformer Carl Lindhagen.
-
E.
Lindesberg
Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
- 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: Hägersten-Liljeholmen Triple: [Söderort, hasPart, Hägersten-Liljeholmen]
Generated description
Hägersten-Liljeholmen is a suburban district and borough in the southern part of Stockholm, Sweden, known for its mix of residential areas, parks, and waterfront along Lake Mälaren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hägersten-Liljeholmen Target entity description: Hägersten-Liljeholmen is a suburban district and borough in the southern part of Stockholm, Sweden, known for its mix of residential areas, parks, and waterfront along Lake Mälaren.
-
A.
Lill-Jansskogen
Lill-Jansskogen is a large urban forest and recreational park area in Stockholm, Sweden, popular for walking, running, and outdoor activities.
-
B.
Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
-
C.
Vingåker
Vingåker is a small locality in Södermanland County, Sweden, known as the hometown of former Swedish Prime Minister Göran Persson.
-
D.
Lindhagen
Lindhagen is a Swedish surname most notably associated with the politician and social reformer Carl Lindhagen.
-
E.
Lindesberg
Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
- 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.