Triple
T9092190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biebrich |
E217916
|
entity |
| Predicate | locatedInRegion |
P40
|
FINISHED |
| Object | Rheingau |
E218115
|
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: Rheingau | Statement: [Biebrich, locatedInRegion, Rheingau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rheingau Context triple: [Biebrich, locatedInRegion, Rheingau]
-
A.
Rheingau
chosen
Rheingau is a renowned German wine region along the Rhine River, especially famous for producing high-quality Riesling wines.
-
B.
Schönbuch
Schönbuch is a large forest and nature reserve in the German state of Baden-Württemberg, known for its extensive woodlands, wildlife, and recreational hiking areas.
-
C.
Pfinz
Pfinz is a river in Baden-Württemberg, Germany, that flows through the northern Black Forest region and the Karlsruhe area before joining the Enz.
-
D.
Eschwege
Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
-
E.
Oberweser
Oberweser is the name given to the upper course of the Weser River in central Germany, encompassing its initial stretch after the confluence of its headstreams.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b18b24819097b525ddad3a85c0 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d017f85c908190a4e90c22a75348b5 |
completed | April 3, 2026, 7:41 p.m. |
Created at: March 30, 2026, 7:14 p.m.