Triple
T11279774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhein-Sieg-Kreis |
E267032
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Siegburg |
E377073
|
NE FINISHED |
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: Siegburg | Statement: [Rhein-Sieg-Kreis, capital, Siegburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siegburg Context triple: [Rhein-Sieg-Kreis, capital, Siegburg]
-
A.
Siegburg
chosen
Siegburg is a historic town in North Rhine-Westphalia, Germany, known for its medieval abbey and location near Bonn and Cologne.
-
B.
Siegenburg
Siegenburg is a market town and municipality in Lower Bavaria, Germany, known for its rural character and location within the Kelheim district.
-
C.
Erftstadt
Erftstadt is a town in the Rhein-Erft district of North Rhine-Westphalia, Germany, located southwest of Cologne and known for its mix of historic villages and suburban residential areas.
-
D.
Siegen
Siegen is a city in western Germany known as the birthplace of the Baroque painter Peter Paul Rubens and for its historic mining and university traditions.
-
E.
Schwerte
Schwerte is a town in North Rhine-Westphalia, Germany, known as a small industrial and commuter community near Dortmund.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e969b3448190940e2bd499d2d7de |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e72931208190b91ef4be770c00d4 |
completed | April 21, 2026, 2:55 a.m. |
Created at: April 8, 2026, 9:31 p.m.