Triple
T5952241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assen |
E132426
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Lingen |
E217689
|
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: Lingen | Statement: [Assen, hasTwinTown, Lingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lingen Context triple: [Assen, hasTwinTown, Lingen]
-
A.
Lingen
chosen
Lingen is a town in Lower Saxony, Germany, known for its location on the River Ems and its role as a regional economic and cultural center.
-
B.
Aurich
Aurich is a historic town in northwestern Germany that serves as one of the principal urban centers of the East Frisia region in Lower Saxony.
-
C.
Wallhausen
Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
-
D.
Lauenburg
Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
-
E.
Heringsdorf
Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03983b8848190afaa37f35c95bad6 |
completed | March 22, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3d1801c819093dc43dc5a525796 |
completed | March 23, 2026, 6:55 a.m. |
Created at: March 22, 2026, 4:02 p.m.