Triple
T19422389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Seseke |
E485888
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Bönen |
—
|
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: Bönen | Statement: [River Seseke, flowsThrough, Bönen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bönen Context triple: [River Seseke, flowsThrough, Bönen]
-
A.
Bönen
chosen
Bönen is a small German town in the state of North Rhine-Westphalia, situated in the Ruhr area between Dortmund and Hamm.
-
B.
Lonstein
Lonstein is a surname of likely Ashkenazi Jewish origin borne by various individuals and families.
-
C.
Bönnsch
Bönnsch is a regional German beer style and dialect variant from Bonn, closely associated with and similar to the Kölsch tradition of nearby Cologne.
-
D.
Borken
Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
-
E.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e632159d7081909d004544ec5992c0 |
completed | April 20, 2026, 2:03 p.m. |
Created at: April 10, 2026, 1:37 p.m.