Triple
T7535263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spree Island |
E178132
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Lustgarten |
E106565
|
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: Lustgarten | Statement: [Spree Island, hasLandmark, Lustgarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lustgarten Context triple: [Spree Island, hasLandmark, Lustgarten]
-
A.
Lustgarten
chosen
Lustgarten is a historic public park and square on Berlin’s Museum Island, long used as a parade ground and gathering place.
-
B.
Riedergarten
Riedergarten is a historic public garden and popular green oasis located in the Bavarian city of Rosenheim, Germany.
-
C.
Wildberg
Wildberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic setting along the Nagold River and historic half-timbered architecture.
-
D.
Syrgenstein
Syrgenstein is a small municipality in the Heidenheim district of the German state of Baden-Württemberg.
-
E.
Schöngarth
Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f84c13208190971096a0b81b0ff2 |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84f0c02148190bb5f63cf9891ec0c |
completed | March 28, 2026, 9:58 p.m. |
Created at: March 27, 2026, 3:47 p.m.