Triple
T18386756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darmstadt Hauptbahnhof |
E446611
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Weiterstadt |
—
|
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: Weiterstadt | Statement: [Darmstadt Hauptbahnhof, connectsWith, Weiterstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weiterstadt Context triple: [Darmstadt Hauptbahnhof, connectsWith, Weiterstadt]
-
A.
Weiterstadt
chosen
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
B.
Oberstedten
Oberstedten is a district of the town Oberursel in Hesse, Germany, situated near the Taunus mountain range.
-
C.
Rudolstadt
Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
-
D.
Augustdorf
Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
-
E.
Korbach
Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
- 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.