Triple
T23014816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havel lakes |
E573001
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Pfaueninsel |
—
|
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: Pfaueninsel | Statement: [Havel lakes, near, Pfaueninsel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pfaueninsel Context triple: [Havel lakes, near, Pfaueninsel]
-
A.
Pfaueninsel
chosen
Pfaueninsel is a small, historic island on the Havel River in Berlin, Germany, known for its romantic landscape park, palace, and free-roaming peacocks.
-
B.
Maximiliansinsel
Maximiliansinsel is a small, picturesque island located in the alpine Eibsee lake at the foot of Germany’s Zugspitze mountain.
-
C.
Luiseninsel
Luiseninsel is a small island and landscaped area within Berlin’s Großer Tiergarten park, known for its tranquil paths and natural scenery.
-
D.
Margaret Island
Margaret Island is a tranquil, park-filled island in the middle of the Danube River in Budapest, known for its recreational facilities, historic ruins, and scenic promenades.
-
E.
Praterinsel
Praterinsel is a small island in the Isar River in central Munich, known for its cultural events, historic buildings, and riverside recreation.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e3c0e08190a7ac747b056ec3ca |
completed | April 29, 2026, 4:06 a.m. |
Created at: April 17, 2026, 3:51 p.m.