Triple
T20456627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erkrath |
E501804
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Alt-Erkrath |
—
|
NE NERFINISHED |
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: Alt-Erkrath | Statement: [Erkrath, hasPart, Alt-Erkrath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alt-Erkrath Context triple: [Erkrath, hasPart, Alt-Erkrath]
-
A.
Erkrath
chosen
Erkrath is a town in the German state of North Rhine-Westphalia, situated near Düsseldorf in the district of Mettmann.
-
B.
Velbert
Velbert is a German city in North Rhine-Westphalia known for its metal and lock manufacturing industry and its location between Düsseldorf, Essen, and Wuppertal.
-
C.
Stolzenhagen
Stolzenhagen is a village and locality within the municipality of Wandlitz in the state of Brandenburg, Germany.
-
D.
Ludwigsfelde
Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
-
E.
Roßdorf
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a1b03c8190984d9db6d3251308 |
completed | April 20, 2026, 9:12 p.m. |
Created at: April 16, 2026, 11:32 a.m.