Triple
T17635800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fallingbostel |
E430089
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Böhme |
—
|
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: Böhme | Statement: [Fallingbostel, locatedOnRiver, Böhme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Böhme Context triple: [Fallingbostel, locatedOnRiver, Böhme]
-
A.
Böhme
chosen
The Böhme is a river in Lower Saxony, Germany, known for flowing through the Lüneburg Heath region before joining the Aller.
-
B.
Rehberg
Rehberg is a district of the Austrian city Krems an der Donau, known for its historic character and location in the Wachau cultural landscape.
-
C.
Kallenbach
Kallenbach is a German-language surname most notably borne by Hermann Kallenbach, a close associate of Mahatma Gandhi.
-
D.
Dehnitz
Dehnitz is a locality within the town of Wurzen in the Free State of Saxony, Germany.
-
E.
Bleichert
Bleichert is a German-origin surname most notably associated with individuals such as Dwight "Bucky" Bleichert, a character in James Ellroy’s crime novel "The Black Dahlia."
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de0ad988190b1a2c0bff69eb9f1 |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 5:52 a.m.