Triple
T13489280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Bahn line S1 |
E318589
|
entity |
| Predicate | via |
P5680
|
FINISHED |
| Object | Steglitz |
E13910
|
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: Steglitz | Statement: [S-Bahn line S1, via, Steglitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steglitz Context triple: [S-Bahn line S1, via, Steglitz]
-
A.
Steglitz-Zehlendorf
chosen
Steglitz-Zehlendorf is a borough in southwestern Berlin known for its affluent residential areas, lakes and forests, and historically significant sites such as the Wannsee Conference villa.
-
B.
Friedrichsfelde
Friedrichsfelde is a residential district in the Berlin borough of Lichtenberg, known for its large housing estates and proximity to Tierpark Berlin.
-
C.
Reinickendorf
Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
-
D.
Pankow
Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
-
E.
Wilmersdorf
Wilmersdorf is a residential district in southwestern Berlin known for its affluent neighborhoods, shopping streets like Kurfürstendamm, and a mix of historic and modern architecture.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3cbe2081908c6792362c67c8f1 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a835ea448190a5ddaf8479e0b36c |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:43 p.m.