Triple
T18386753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darmstadt Hauptbahnhof |
E446611
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Bensheim |
—
|
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: Bensheim | Statement: [Darmstadt Hauptbahnhof, connectsWith, Bensheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bensheim Context triple: [Darmstadt Hauptbahnhof, connectsWith, Bensheim]
-
A.
Bensheim
chosen
Bensheim is a historic town in southern Hesse, Germany, known for its wine-growing tradition and picturesque location on the Bergstraße at the edge of the Odenwald.
-
B.
Weinheim
Weinheim is a historic town in southwestern Germany, known for its picturesque old town, twin castles, and location on the Bergstraße at the edge of the Odenwald.
-
C.
Weikersheim
Weikersheim is a small historic town in the Tauber Valley of Baden-Württemberg, Germany, known for its Renaissance castle and well-preserved old town.
-
D.
Bruchsal
Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
-
E.
Uffenheim
Uffenheim is a small town in the Franconian region of northern Bavaria, Germany, known for its historic architecture and rural surroundings.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517a00c608190a8f0010c7b53df90 |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 10:46 a.m.