Triple
T17050171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauda-Königshofen |
E413673
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tauber Valley |
E413662
|
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: Tauber Valley | Statement: [Lauda-Königshofen, locatedIn, Tauber Valley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tauber Valley Context triple: [Lauda-Königshofen, locatedIn, Tauber Valley]
-
A.
Tauber Valley
chosen
The Tauber Valley is a picturesque river valley in southern Germany known for its medieval towns, vineyards, and scenic cycling and hiking routes.
-
B.
Shigal Valley
Shigal Valley is a mountainous river valley in eastern Afghanistan known for its rugged terrain, strategic location, and proximity to the Pakistan border.
-
C.
Zechawa Valley
Zechawa Valley is one of the main scenic valleys in China’s Jiuzhaigou National Park, known for its high-altitude lakes, waterfalls, and colorful alpine landscapes.
-
D.
Weingarten region
The Weingarten region is a historical area in present-day Germany known for its monastic heritage and wine-producing landscapes.
-
E.
Elmstein valley
Elmstein valley is a scenic, forested valley in Germany’s Palatinate region, known for its hiking trails, historic villages, and preserved narrow-gauge railway.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa1aeac81909e8d97bd708c6b71 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fbb89fc81908d2355d36ea2469e |
completed | May 11, 2026, 4:48 a.m. |
Created at: April 10, 2026, 5:34 a.m.