Triple
T20037777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schöneberg |
E497321
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object | Rote Insel |
—
|
NE NERFINISHED |
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: Rote Insel | Statement: [Schöneberg, hasNeighbourhood, Rote Insel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rote Insel Context triple: [Schöneberg, hasNeighbourhood, Rote Insel]
-
A.
Rote Insel
chosen
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.
-
B.
Roseninsel
Roseninsel is a small, historically significant island in Lake Starnberg in Bavaria, Germany, known for its rose gardens and former royal retreat.
-
C.
Rote Island
Rote Island is a small Indonesian island in the southernmost part of the country, known for its traditional culture, dry landscapes, and surf-friendly beaches.
-
D.
Schnäggeninseli
Schnäggeninseli is a small, picturesque island in Switzerland’s Lake Brienz, known for its natural beauty and tranquil setting.
-
E.
Humboldt-Insel
Humboldt-Insel is a small island in Berlin’s Spree River, known for its residential areas and proximity to the city’s central districts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e935ac8190900cdb4f0cfde505 |
completed | April 20, 2026, 5:31 p.m. |
Created at: April 11, 2026, 3:36 p.m.