Triple
T15563348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther Church Plauen |
E371051
|
entity |
| Predicate | locatedInUrbanArea |
P12103
|
FINISHED |
| Object | city of Plauen |
E1162173
|
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: city of Plauen | Statement: [Luther Church Plauen, locatedInUrbanArea, city of Plauen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Plauen Context triple: [Luther Church Plauen, locatedInUrbanArea, city of Plauen]
-
A.
City of Plauen
chosen
The City of Plauen is a German municipality in the Free State of Saxony, known historically for its textile and lace industry and its location in the Vogtland region.
-
B.
Plüderhausen
Plüderhausen is a municipality in the German state of Baden-Württemberg, located in the Rems Valley east of Stuttgart.
-
C.
Riedenburg
Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
-
D.
Kronach
Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
-
E.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddc66448190948280fb0c8d390c |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456821988190971539b683f6c656 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.