Triple
T17157403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remscheid-Lennep station |
E416379
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lennep |
E92687
|
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: Lennep | Statement: [Remscheid-Lennep station, locatedIn, Lennep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lennep Context triple: [Remscheid-Lennep station, locatedIn, Lennep]
-
A.
Lennep
chosen
Lennep is a historic district of the German city of Remscheid in North Rhine-Westphalia, known as the birthplace of physicist Wilhelm Röntgen.
-
B.
Lennep district
Lennep district is a borough of the city of Remscheid in North Rhine-Westphalia, Germany, known for its historic town center and traditional half-timbered architecture.
-
C.
Leppe
Leppe is a small river in western Germany that flows through the hilly Bergisches Land region of North Rhine-Westphalia.
-
D.
Lennestadt
Lennestadt is a town in the Olpe district of North Rhine-Westphalia, Germany, known for its location in the hilly, forested Sauerland region and its mix of industry and tourism.
-
E.
Lokstedt
Lokstedt is a district in the Eimsbüttel borough of Hamburg, Germany, known for its residential character and the presence of major broadcasting facilities.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40bf9ec8190b16372bcd091db9b |
completed | April 18, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fc46c308190b09efb13776747e7 |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:37 a.m.