Triple
T22259707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holtemme |
E550185
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Blankenburg am Harz |
—
|
NE NERFINISHED |
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: Blankenburg am Harz | Statement: [Holtemme, flowsThrough, Blankenburg am Harz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blankenburg am Harz Context triple: [Holtemme, flowsThrough, Blankenburg am Harz]
-
A.
Blankenburg (Harz)
chosen
Blankenburg (Harz) is a historic town in the Harz Mountains of central Germany, known for its medieval castle, scenic landscapes, and traditional architecture.
-
B.
Herzberg am Harz
Herzberg am Harz is a small town in Lower Saxony, Germany, located on the southern edge of the Harz Mountains and known for its historic castle and timber-framed architecture.
-
C.
Boltenhagen
Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
-
D.
Benneckenstein (Harz)
Benneckenstein (Harz) is a small town in the Harz Mountains of central Germany, now incorporated into the town of Oberharz am Brocken.
-
E.
Haldensleben
Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c5b54c8190854690ba599639fa |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.