Triple
T1300123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Södermanland County |
E27742
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
|
E176028
|
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: Strängnäs | Statement: [Södermanland County, contains, Strängnäs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strängnäs Context triple: [Södermanland County, contains, Strängnäs]
-
A.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
Västerhaninge
Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
-
D.
Trollhättan
Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
-
E.
Nyköping
Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
- 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: Strängnäs Triple: [Södermanland County, contains, Strängnäs]
Generated description
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Strängnäs Target entity description: Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
A.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
B.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
C.
Västerhaninge
Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
-
D.
Trollhättan
Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
-
E.
Nyköping
Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c11314a48190ab4efb8b1acdce50 |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad3083a3748190b2404ef5edf90fd7 |
completed | March 8, 2026, 8:17 a.m. |
| NEDg | Description generation | batch_69ad31dcdef0819093276857b247ecea |
completed | March 8, 2026, 8:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad32f287008190b66c9e626a0f39f1 |
completed | March 8, 2026, 8:27 a.m. |
Created at: March 1, 2026, 7:51 p.m.