Triple
T6201407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Rostock |
E138640
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Grevesmühlen |
E287279
|
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: Grevesmühlen | Statement: [Bezirk Rostock, contains, Grevesmühlen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grevesmühlen Context triple: [Bezirk Rostock, contains, Grevesmühlen]
-
A.
Grevesmühlen
chosen
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.
-
B.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
C.
Brandenburg an der Havel
Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
-
D.
Zossen
Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after World War II.
-
E.
Ribnitz-Damgarten
Ribnitz-Damgarten is a small town in northeastern Germany known as the “Bernsteinstadt” (Amber Town) for its long tradition of amber processing and its location near the Baltic Sea.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062559bcc81908942bb4d25fe8158 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d96415c8190b0c5c7f9fd19f5be |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:20 p.m.