Triple
T20236218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerstetten |
E498153
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Roßdorf |
—
|
NE NERFINISHED |
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: Roßdorf | Statement: [Gerstetten, hasTwinTown, Roßdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roßdorf Context triple: [Gerstetten, hasTwinTown, Roßdorf]
-
A.
Roßdorf
chosen
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
-
B.
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.
-
C.
Frohnau
Frohnau is a residential district in northern Berlin known for its garden city layout and good public transport connections.
-
D.
Oranienburger Vorstadt
Oranienburger Vorstadt is a historic neighborhood in central Berlin, known for its 19th-century urban fabric, cultural sites, and proximity to key political and intellectual centers of the city.
-
E.
Schönewalde
Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716a5af0819095ea419a4d1f0d1d |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.