Triple
T1839156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiemsee |
E41133
|
entity |
| Predicate | hasIsland |
P970
|
FINISHED |
| Object | Krautinsel |
E206839
|
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: Krautinsel | Statement: [Chiemsee, hasIsland, Krautinsel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krautinsel Context triple: [Chiemsee, hasIsland, Krautinsel]
-
A.
Krautinsel
chosen
Krautinsel is a small, uninhabited island in Germany’s Chiemsee lake, historically used for agriculture and known for its tranquil natural setting.
-
B.
Island of Usedom
The Island of Usedom is a Baltic Sea island shared by Germany and Poland, renowned for its long sandy beaches, seaside resorts, and status as a popular holiday destination.
-
C.
Rote Insel
Rote Insel is a distinctive, historically working-class neighborhood in Berlin known for its island-like layout encircled by railway lines and its rich social and cultural history.
-
D.
Helgoland
Helgoland is a small German archipelago in the North Sea known for its dramatic red sandstone cliffs, unique wildlife, and historical significance as a strategic naval and cultural site.
-
E.
Rügen
Rügen is Germany’s largest island, known for its chalk cliffs, seaside resorts, and beaches along the Baltic Sea coast.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb03b3eb08190ae68d8476fc89c7f |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1c482908190b940497fc5d5db60 |
completed | March 8, 2026, 7:45 p.m. |
Created at: March 4, 2026, 7:33 p.m.