Triple
T6623110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leszno |
E149724
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Nässjö
Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
|
E606259
|
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: Nässjö | Statement: [Leszno, hasTwinTown, Nässjö]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nässjö Context triple: [Leszno, hasTwinTown, Nässjö]
-
A.
Tärnsjö
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Nykvarn
Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
-
D.
Svalöv
Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
-
E.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
- 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: Nässjö Triple: [Leszno, hasTwinTown, Nässjö]
Generated description
Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nässjö Target entity description: Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
-
A.
Tärnsjö
Tärnsjö is a small locality in central Sweden known for its rural setting and traditional leather tanning industry.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Nykvarn
Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
-
D.
Svalöv
Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
-
E.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af7decb08190a7b1ddb95e534a6a |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e44b251481909dca5ff82e1dbf0f |
completed | March 27, 2026, 8:10 p.m. |
| NEDg | Description generation | batch_69c6e52ba51c81908439acc1a4af9d6e |
completed | March 27, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e5b6e6f48190a813fcd1473be4e1 |
completed | March 27, 2026, 8:16 p.m. |
Created at: March 27, 2026, 1:58 p.m.