Triple
T9123531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teutoburg Forest region |
E218916
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bad Driburg |
E195900
|
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: Bad Driburg | Statement: [Teutoburg Forest region, contains, Bad Driburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Driburg Context triple: [Teutoburg Forest region, contains, Bad Driburg]
-
A.
Bad Driburg
chosen
Bad Driburg is a small spa town in North Rhine-Westphalia, Germany, known for its mineral springs and health resorts.
-
B.
Bad Godesberg
Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
-
C.
Brühl
Brühl is a German town in North Rhine-Westphalia known for its historic architecture and as the birthplace of surrealist artist Max Ernst.
-
D.
Grevesmühlen
Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
-
E.
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.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d047c55a988190bf2dd63a0d0a2743 |
completed | April 3, 2026, 11:05 p.m. |
Created at: March 30, 2026, 7:17 p.m.