Triple
T16293105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unna district |
E395574
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Fröndenberg |
E456760
|
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: Fröndenberg | Statement: [Unna district, containsTown, Fröndenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fröndenberg Context triple: [Unna district, containsTown, Fröndenberg]
-
A.
Fröndenberg
chosen
Fröndenberg is a small town in North Rhine-Westphalia, Germany, situated on the Ruhr River and known for its scenic rural surroundings.
-
B.
Frankenberg
Frankenberg is a town in the German state of Hesse, historically notable as the place where King Conrad I of Germany died.
-
C.
Gödringen
Gödringen is a village and district of the town of Sarstedt in Lower Saxony, Germany.
-
D.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
E.
Hademstorf
Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2aee6881909fd28547f135427c |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f97895081909f22ded3507afe14 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:05 a.m.