Triple
T4445758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wadern |
E96280
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
|
E443556
|
NE FINISHED |
How this triple was built (4 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: Löstertal | Statement: [Wadern, hasSubdivision, Löstertal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löstertal Context triple: [Wadern, hasSubdivision, Löstertal]
-
A.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
-
B.
Sihltal
Sihltal is a Swiss valley in the canton of Zurich shaped by the Sihl River, known for its scenic landscapes and proximity to the city of Zurich.
-
C.
Luterbach
Luterbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Aare River.
-
D.
Weidach
Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
-
E.
Wahnbach
Wahnbach is a small river in North Rhine-Westphalia, Germany, known for feeding the Wahnbach Dam and serving as a tributary of the Sieg.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Löstertal Triple: [Wadern, hasSubdivision, Löstertal]
Generated description
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Löstertal Target entity description: Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
A.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
-
B.
Sihltal
Sihltal is a Swiss valley in the canton of Zurich shaped by the Sihl River, known for its scenic landscapes and proximity to the city of Zurich.
-
C.
Luterbach
Luterbach is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Aare River.
-
D.
Weidach
Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
-
E.
Wahnbach
Wahnbach is a small river in North Rhine-Westphalia, Germany, known for feeding the Wahnbach Dam and serving as a tributary of the Sieg.
- F. None of above. chosen
Provenance (5 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d1eba08190899d0a3c1684ce4e |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6376286e48190906874d67c730dc9 |
completed | March 15, 2026, 4:36 a.m. |
| NEDg | Description generation | batch_69b63834bacc8190b5d81723cabc2da7 |
completed | March 15, 2026, 4:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b638b105e88190a02c515a3416a026 |
completed | March 15, 2026, 4:42 a.m. |
Created at: March 12, 2026, 11:32 p.m.