Triple
T14723792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schloss Reinhartshausen |
E345882
|
entity |
| Predicate | locatedIn |
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: [Schloss Reinhartshausen, locatedIn, Rheingau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rheingau Context triple: [Schloss Reinhartshausen, locatedIn, Rheingau]
-
A.
Rheingau
chosen
Rheingau is a renowned German wine region along the Rhine River, especially famous for producing high-quality Riesling wines.
-
B.
Rheintal
Rheintal is a region in eastern Switzerland along the Rhine River, known for its valleys, towns, and cross-border connections with neighboring countries.
-
C.
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.
-
D.
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.
-
E.
Eschwege
Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25e9a14819081fa06fc601f295d |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb8624bc8190b20441c2f5c4a2fa |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.