Triple
T18184607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Peter’s Church in Klippan |
E435376
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Klippan
Klippan is a locality and municipal seat in Skåne County in southern Sweden, known for its historic church and small-town character.
|
E1311387
|
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: Klippan | Statement: [St Peter’s Church in Klippan, locatedIn, Klippan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klippan Context triple: [St Peter’s Church in Klippan, locatedIn, Klippan]
-
A.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
-
B.
Kluuvi
Kluuvi is a central district of Helsinki, Finland, known as the city’s main commercial and business hub.
-
C.
Kastlösa
Kastlösa is a small village on the island of Öland in southeastern Sweden, known for its rural landscape and traditional agricultural surroundings.
-
D.
Karlaplan
Karlaplan is a prominent circular plaza and park with a central fountain in the Östermalm district of Stockholm, Sweden.
-
E.
Strandebarm
Strandebarm is a small village in western Norway, situated along the Hardangerfjord in Kvam municipality in Vestland county.
- 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: Klippan Triple: [St Peter’s Church in Klippan, locatedIn, Klippan]
Generated description
Klippan is a locality and municipal seat in Skåne County in southern Sweden, known for its historic church and small-town character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Klippan Target entity description: Klippan is a locality and municipal seat in Skåne County in southern Sweden, known for its historic church and small-town character.
-
A.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
-
B.
Kluuvi
Kluuvi is a central district of Helsinki, Finland, known as the city’s main commercial and business hub.
-
C.
Kastlösa
Kastlösa is a small village on the island of Öland in southeastern Sweden, known for its rural landscape and traditional agricultural surroundings.
-
D.
Karlaplan
Karlaplan is a prominent circular plaza and park with a central fountain in the Östermalm district of Stockholm, Sweden.
-
E.
Strandebarm
Strandebarm is a small village in western Norway, situated along the Hardangerfjord in Kvam municipality in Vestland county.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffd0abc81908cc07d28bdc3d48f |
completed | April 19, 2026, 2 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0398032e3081909455845718c73b78 |
completed | May 12, 2026, 9:13 p.m. |
| NEDg | Description generation | batch_6a03990a2bec8190b5d6a472bc9bb3fb |
completed | May 12, 2026, 9:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0399c98a88819090e579324d9423e5 |
completed | May 12, 2026, 9:21 p.m. |
Created at: April 10, 2026, 10:31 a.m.