Triple
T14295435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Berlin |
E354425
|
entity |
| Predicate | containsGreenArea |
P45219
|
FINISHED |
| Object | Mauerpark |
E393555
|
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: Mauerpark | Statement: [Northern Berlin, containsGreenArea, Mauerpark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mauerpark Context triple: [Northern Berlin, containsGreenArea, Mauerpark]
-
A.
Mauerpark
chosen
Mauerpark is a popular public park and cultural hotspot in Berlin, known for its lively flea market, street performances, and open-air karaoke.
-
B.
Volkspark Prenzlauer Berg
Volkspark Prenzlauer Berg is a large public park in Berlin known for its landscaped hills, walking paths, and recreational green spaces.
-
C.
Schillerpark
Schillerpark is a historic public park in Berlin known for its expansive lawns, tree-lined paths, and role as a popular recreational area for local residents.
-
D.
Volkspark Friedrichshain
Volkspark Friedrichshain is a large historic public park in Berlin known for its wooded hills, walking paths, and recreational facilities.
-
E.
Hansaplatz
Hansaplatz is a Berlin U-Bahn station on the U9 line located in the Hansaviertel district of the city.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717b35ec81908968994e65737c66 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5504dc6c8190a4d8a5985632901d |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:11 a.m.