Triple
T2136261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandenburg |
E46660
|
entity |
| Predicate | hasLargestCity |
P235
|
FINISHED |
| Object | Potsdam |
E13693
|
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: Potsdam | Statement: [Brandenburg, hasLargestCity, Potsdam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Potsdam Context triple: [Brandenburg, hasLargestCity, Potsdam]
-
A.
Potsdam
chosen
Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
-
B.
Neustrelitz
Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
-
C.
Brandenburg an der Havel
Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
-
D.
Spandau
Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
-
E.
Dresden
Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbdc4ce8c81908d143d5451681e6a |
completed | March 7, 2026, 5:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5cbcf8dc8190a3319bdf58dce307 |
completed | March 9, 2026, 11:50 p.m. |
Created at: March 4, 2026, 7:44 p.m.