Triple
T15040419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Söderort |
E378584
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Örnsberg
Örnsberg is a residential district in southern Stockholm, Sweden, known for its proximity to Lake Mälaren and its mix of older and modern housing.
|
E1132945
|
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: Örnsberg | Statement: [Söderort, hasPart, Örnsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Örnsberg Context triple: [Söderort, hasPart, Örnsberg]
-
A.
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
-
B.
Örebro
Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Falkenberg
Falkenberg is a coastal town in southwestern Sweden known for its beaches, fishing heritage, and location along the River Ätran.
-
E.
Falkenberg
Falkenberg is a small municipality in the Rottal-Inn district of Lower Bavaria in southeastern Germany.
- 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: Örnsberg Triple: [Söderort, hasPart, Örnsberg]
Generated description
Örnsberg is a residential district in southern Stockholm, Sweden, known for its proximity to Lake Mälaren and its mix of older and modern housing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Örnsberg Target entity description: Örnsberg is a residential district in southern Stockholm, Sweden, known for its proximity to Lake Mälaren and its mix of older and modern housing.
-
A.
Oskarshamn
Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
-
B.
Örebro
Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
-
C.
Karlskoga
Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
-
D.
Falkenberg
Falkenberg is a coastal town in southwestern Sweden known for its beaches, fishing heritage, and location along the River Ätran.
-
E.
Falkenberg
Falkenberg is a small municipality in the Rottal-Inn district of Lower Bavaria in southeastern Germany.
- 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.