Triple
T20863246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mörfelden-Walldorf |
E513679
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Groß-Gerau |
—
|
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: Groß-Gerau | Statement: [Mörfelden-Walldorf, district, Groß-Gerau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groß-Gerau Context triple: [Mörfelden-Walldorf, district, Groß-Gerau]
-
A.
Groß-Gerau
chosen
Groß-Gerau is a town in the German state of Hesse that serves as the administrative seat of the Groß-Gerau district in the Rhine-Main region.
-
B.
Gelnhausen
Gelnhausen is a historic town in the German state of Hesse, known for its well-preserved medieval architecture and former status as a Free Imperial City of the Holy Roman Empire.
-
C.
Neu-Isenburg
Neu-Isenburg is a town in the Offenbach district of Hesse, Germany, located near Frankfurt am Main and known for its residential character and proximity to major transport routes.
-
D.
Külsheim
Külsheim is a small town in the Main-Tauber district of Baden-Württemberg in southwestern Germany, known for its historic center and surrounding rural landscape.
-
E.
Nussloch
Nussloch is a small town in southwestern Germany, known in part for hosting the headquarters of medical technology company Leica Biosystems.
- 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_69e0b4f5b01081909452f654d2fc3f50 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c45d2ec4819098abbb901b9fcd87 |
completed | April 21, 2026, 12:27 a.m. |
Created at: April 16, 2026, 12:44 p.m.