Triple
T10634454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergkamen |
E250540
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Hettstedt |
E896414
|
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: Hettstedt | Statement: [Bergkamen, hasTwinTown, Hettstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hettstedt Context triple: [Bergkamen, hasTwinTown, Hettstedt]
-
A.
Hettstedt
chosen
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Stedesdorf
Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
-
D.
Hennigsdorf
Hennigsdorf is a town in the German state of Brandenburg, located just northwest of Berlin and known for its industrial heritage and proximity to the Havel River.
-
E.
Ballenstedt
Ballenstedt is a historic town in the German state of Saxony-Anhalt, known for its castle and location on the northern edge of the Harz Mountains.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfab47bc819086684edc1b6dce74 |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e877c6188190817fb30f2c9a07bf |
completed | April 20, 2026, 8:48 a.m. |
Created at: April 8, 2026, 9:03 p.m.