Triple
T5857744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Chapel |
E130195
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Riddarholmen |
E132299
|
NE FINISHED |
How this triple was built (2 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: Riddarholmen | Statement: [Caroline Chapel, locatedIn, Riddarholmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riddarholmen Context triple: [Caroline Chapel, locatedIn, Riddarholmen]
-
A.
Riddarholmen
chosen
Riddarholmen is a small historic island in central Stockholm, Sweden, known for its medieval architecture, royal burial church, and role as part of the city’s old town district.
-
B.
Strömsborg
Strömsborg is a small islet in central Stockholm, Sweden, known for its historic buildings and picturesque waterfront setting near the Old Town.
-
C.
Kungsholmen
Kungsholmen is a central island and district of Stockholm known for its waterfront promenades, residential areas, and the iconic Stockholm City Hall.
-
D.
Lindholmen
Lindholmen is a small locality in Vallentuna Municipality in Stockholm County, Sweden, known for its residential character and proximity to natural and historical sites.
-
E.
Lindholmen
Lindholmen is a waterfront district in Gothenburg, Sweden, known as a major hub for education, research, and technology companies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0355755508190ab349cdcf0c8a58d |
completed | March 22, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b105fb588190ac58a94513df6682 |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:56 p.m.