Triple
T2502660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brückenstraße (Chemnitz) |
E52499
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Brueckenstrasse@de-ASCII |
E52499
|
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: Brueckenstrasse@de-ASCII | Statement: [Brückenstraße (Chemnitz), hasNameInLanguage, Brueckenstrasse@de-ASCII]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brueckenstrasse@de-ASCII Context triple: [Brückenstraße (Chemnitz), hasNameInLanguage, Brueckenstrasse@de-ASCII]
-
A.
Brückenstraße
chosen
Brückenstraße is a street in Chemnitz, Germany, known for being the prominent urban backdrop in front of the iconic Karl Marx Monument.
-
B.
Paradestraße
Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
-
C.
Breite Straße
Breite Straße is a historic main street in the medieval town of Goslar, Germany, known for its traditional half-timbered houses and central role in the old town.
-
D.
Julius-Leber-Brücke station
Julius-Leber-Brücke station is a Berlin S-Bahn railway stop located in the Schöneberg district of Germany’s capital.
-
E.
Kaufingerstraße
Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cb4f6481908d4e0a1dc0d84d3c |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1fa34dc8819085681d673e45d841 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.