Triple
T12033803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frechen |
E286481
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Hürth |
E691066
|
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: Hürth | Statement: [Frechen, hasNeighbouringMunicipality, Hürth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hürth Context triple: [Frechen, hasNeighbouringMunicipality, Hürth]
-
A.
Hürth
chosen
Hürth is a town in North Rhine-Westphalia, Germany, best known internationally as the birthplace of Formula One legend Michael Schumacher.
-
B.
Hennef
Hennef is a town in North Rhine-Westphalia, Germany, situated on the river Sieg near Bonn and known for its mix of residential areas, industry, and surrounding countryside.
-
C.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
D.
Meckenheim
Meckenheim is a town in the Rhein-Sieg district of North Rhine-Westphalia, Germany, known for its fruit cultivation and proximity to Bonn.
-
E.
Solingen
Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af3b91288190ab2df6103bfa5a91 |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 8, 2026, 9:47 p.m.