Triple
T8439307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhine-Ruhr metropolitan region |
E199309
|
entity |
| Predicate | containsCity |
P294
|
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: [Rhine-Ruhr metropolitan region, containsCity, Siegburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siegburg Context triple: [Rhine-Ruhr metropolitan region, containsCity, 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.
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.
-
C.
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.
-
D.
Schwerte
Schwerte is a town in North Rhine-Westphalia, Germany, known as a small industrial and commuter community near Dortmund.
-
E.
Friedeburg
Friedeburg is a small municipality in Lower Saxony, Germany, known for its rural character and location within the East Frisian region.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe13708988190a534e38d8254c9bd |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d9140b48190ad0c493948a3de5e |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.