Triple
T15092087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skaraborg County |
E360443
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Grästorp |
E1137637
|
NE FINISHED |
How this triple was built (2 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: Grästorp | Statement: [Skaraborg County, contains, Grästorp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grästorp Context triple: [Skaraborg County, contains, Grästorp]
-
A.
Gnesta
Gnesta is a small town in Södermanland County, Sweden, known for its lakeside setting and role as a local commercial and transport hub.
-
B.
Gerstad
Gerstad is a surname most notably associated with Harry W. Gerstad, an American film editor who won Academy Awards for his work.
-
C.
Västertorp
Västertorp is a residential district in southern Stockholm, Sweden, known for its mid-20th-century architecture and public sculptures.
-
D.
Löttorp
Löttorp is a small village and local service center located on the Baltic Sea island of Öland in southeastern Sweden.
-
E.
Grästorp Municipality
chosen
Grästorp Municipality is a local government area in western Sweden known for its rural landscape and agricultural character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027925788190b955fdc6626adf7d |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7e47b20819084145008474f47b7 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:04 a.m.