Triple
T5500038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gnesta Municipality |
E144303
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object |
Gnesta
Gnesta is a small town in Södermanland County, Sweden, known for its lakeside setting and role as a local commercial and transport hub.
|
E529866
|
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: Gnesta | Statement: [Gnesta Municipality, seat, Gnesta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gnesta Context triple: [Gnesta Municipality, seat, Gnesta]
-
A.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
B.
Gnesta Municipality
Gnesta Municipality is a local government area in Södermanland County, Sweden, known for its small-town character, lakes, and proximity to the Stockholm region.
-
C.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
- 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: Gnesta Triple: [Gnesta Municipality, seat, Gnesta]
Generated description
Gnesta is a small town in Södermanland County, Sweden, known for its lakeside setting and role as a local commercial and transport hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gnesta Target entity description: Gnesta is a small town in Södermanland County, Sweden, known for its lakeside setting and role as a local commercial and transport hub.
-
A.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
B.
Gnesta Municipality
Gnesta Municipality is a local government area in Södermanland County, Sweden, known for its small-town character, lakes, and proximity to the Stockholm region.
-
C.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
- 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01b921884819082fe30100c71e516 |
completed | March 22, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02796cac88190abd8d58eb7ae1267 |
completed | March 22, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69c034158a148190b9b63d7e5e65303f |
completed | March 22, 2026, 6:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c034a04d708190922acece40008d7b |
completed | March 22, 2026, 6:27 p.m. |
Created at: March 22, 2026, 3:32 p.m.