Triple
T20046698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groß-Gerau district |
E497576
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Raunheim |
—
|
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: Raunheim | Statement: [Groß-Gerau district, contains, Raunheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raunheim Context triple: [Groß-Gerau district, contains, Raunheim]
-
A.
Raunheim
chosen
Raunheim is a town in the German state of Hesse, located near Frankfurt am Main and known for its proximity to major transportation routes and Frankfurt Airport.
-
B.
Rüttenscheid
Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
-
C.
Burscheid
Burscheid is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its mix of rural character and local industry.
-
D.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
E.
Würselen
Würselen is a town in western Germany’s state of North Rhine-Westphalia, located near the city of Aachen and known historically for its mining and industrial heritage.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632b2de48190abe2b277d89eb695 |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:37 p.m.