Triple
T8337654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hattingen |
E195827
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Altstadt Hattingen |
E195827
|
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: Altstadt Hattingen | Statement: [Hattingen, hasLandmark, Altstadt Hattingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altstadt Hattingen Context triple: [Hattingen, hasLandmark, Altstadt Hattingen]
-
A.
Hattingen
chosen
Hattingen is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval old town and its location in the Ruhr industrial region.
-
B.
Heinsberg
Heinsberg is a town in western Germany’s North Rhine-Westphalia near the Dutch border, known as the administrative center of the Heinsberg district.
-
C.
Schlettstadt
Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
-
D.
Hennef
Hennef is a town in North Rhine-Westphalia, Germany, situated on the river Sieg near Bonn and known for its mix of residential areas, industry, and surrounding countryside.
-
E.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd5027c81909724f25aa30bbe58 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95e4382081908634f31eb115e557 |
completed | April 1, 2026, 10:02 p.m. |
Created at: March 30, 2026, 5:57 p.m.