Triple
T9942333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmersdorf |
E194112
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Berliner Straße |
E444705
|
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: Berliner Straße | Statement: [Wilmersdorf, hasLandmark, Berliner Straße]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berliner Straße Context triple: [Wilmersdorf, hasLandmark, Berliner Straße]
-
A.
Berliner Straße
chosen
Berliner Straße is a major Berlin U-Bahn station complex in the district of Wilmersdorf, serving as a key transfer point between multiple subway lines.
-
B.
Berliner Straße
Berliner Straße is a central street in the historic city of Görlitz, Germany, known for its traditional urban architecture and role as a key thoroughfare near the Obermarkt.
-
C.
Perusastraße
Perusastraße is a street in central Munich, Germany, located near Odeonsplatz in the historic city center.
-
D.
Schönhauser Allee
Schönhauser Allee is a major transport hub and street in Berlin’s Prenzlauer Berg district, served by both the city’s S-Bahn and U-Bahn networks.
-
E.
Leipziger Straße
Leipziger Straße is a major historic thoroughfare in central Berlin, known for its government buildings, commercial centers, and role in the city’s urban core.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6124a188190b41feadb7b2f8922 |
completed | April 2, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257986a648190b72697e4644c9c1c |
completed | April 5, 2026, 12:37 p.m. |
Created at: March 30, 2026, 8:45 p.m.