Triple
T15420507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DEL |
E369361
|
entity |
| Predicate | registrationArea |
P48529
|
FINISHED |
| Object | Delmenhorst |
E75428
|
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: Delmenhorst | Statement: [DEL, registrationArea, Delmenhorst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delmenhorst Context triple: [DEL, registrationArea, Delmenhorst]
-
A.
Delmenhorst
chosen
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
B.
Wallenhorst
Wallenhorst is a municipality in Lower Saxony, Germany, located near the city of Osnabrück.
-
C.
Nordhorn
Nordhorn is a town in Lower Saxony, Germany, known as the administrative center of the Grafschaft Bentheim district near the Dutch border.
-
D.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
-
E.
Norderstedt
Norderstedt is a city in northern Germany that forms part of the Hamburg metropolitan area and is one of the larger urban centers in the state of Schleswig-Holstein.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ebe7b1081908e6b9e6e128a8d5d |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139e10e94819092b71606dbe4f5d5 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 3:20 a.m.