Triple
T16408754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krefeld |
E398502
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Bockum |
E191564
|
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: Bockum | Statement: [Krefeld, hasDistrict, Bockum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bockum Context triple: [Krefeld, hasDistrict, Bockum]
-
A.
Bockum
chosen
Bockum is a residential district of the German city of Krefeld, known for its green spaces and affluent neighborhoods.
-
B.
Bockenem
Bockenem is a small town in Lower Saxony, Germany, known for its rural character and location within the Hildesheim district.
-
C.
Brinkum
Brinkum is a small municipality in the Leer district of Lower Saxony in northwestern Germany.
-
D.
Halstenbek
Halstenbek is a municipality in the district of Pinneberg in Schleswig-Holstein, northern Germany, known as a residential suburb on the western outskirts of Hamburg.
-
E.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
- 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.