Triple
T16408769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krefeld |
E398502
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Dünkirchen |
E182674
|
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: Dünkirchen | Statement: [Krefeld, twinTown, Dünkirchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dünkirchen Context triple: [Krefeld, twinTown, Dünkirchen]
-
A.
Dunker
Dunker is the costumed racehorse mascot that represents Murray State University at its athletic events and campus activities.
-
B.
Cuxhaven
Cuxhaven is a German port city on the North Sea coast that historically served as an important naval and maritime hub.
-
C.
Duinkerke
chosen
Duinkerke is the Dutch name for Dunkirk, a historic port city in northern France known for its pivotal World War II evacuation.
-
D.
Warburg
Warburg is a historic small city in the German state of Hesse, known for its well-preserved medieval old town and hilltop castle.
-
E.
Warburg
Warburg is a prominent German-Jewish banking and philanthropic family historically influential in international finance and economic policy.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32870e44c8190aae7bc6e6022ceb7 |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c64a05c8190a59e800ce2318052 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:09 a.m.