Triple
T4821346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västergötland |
E107715
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Varnhem
Varnhem is a historic village in southwestern Sweden best known for its medieval abbey ruins and significant archaeological sites.
|
E475435
|
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: Varnhem | Statement: [Västergötland, containsTown, Varnhem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varnhem Context triple: [Västergötland, containsTown, Varnhem]
-
A.
Vänersborg
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
-
D.
Mönsterås
Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
-
E.
Västerhaninge
Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
- 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: Varnhem Triple: [Västergötland, containsTown, Varnhem]
Generated description
Varnhem is a historic village in southwestern Sweden best known for its medieval abbey ruins and significant archaeological sites.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Varnhem Target entity description: Varnhem is a historic village in southwestern Sweden best known for its medieval abbey ruins and significant archaeological sites.
-
A.
Vänersborg
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
-
D.
Mönsterås
Mönsterås is a small coastal town and municipality in Kalmar County, southeastern Sweden, known for its Baltic Sea shoreline and traditional Swedish countryside.
-
E.
Västerhaninge
Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c99b46c8190b6fbcf9f98b9e993 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cb34004819086809b4a7071f4a5 |
completed | March 21, 2026, 8:54 a.m. |
| NEDg | Description generation | batch_69be607df6648190be22b5bc0d6531b4 |
completed | March 21, 2026, 9:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be611da7c08190b644cfbcb30741fc |
completed | March 21, 2026, 9:13 a.m. |
Created at: March 20, 2026, 1:24 p.m.