Triple
T10892340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steinfurt (district) |
E257209
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Hörstel
Hörstel is a small town in North Rhine-Westphalia, Germany, known for its location near the Teutoburg Forest and the Dortmund–Ems Canal.
|
E892783
|
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: Hörstel | Statement: [Steinfurt (district), contains, Hörstel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hörstel Context triple: [Steinfurt (district), contains, Hörstel]
-
A.
Hörsel
Hörsel is a river in central Germany that flows through Thuringia and joins the Werra, contributing to the region’s drainage system.
-
B.
Hademstorf
Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
-
C.
Hohneck
Hohneck is one of the highest peaks in the Vosges Mountains of northeastern France, known for its panoramic views and popular hiking and skiing opportunities.
-
D.
Bernlohe
Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
-
E.
Geiselhöring
Geiselhöring is a small town in Lower Bavaria, Germany, known for its rural character and location within the Straubing-Bogen district.
- 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: Hörstel Triple: [Steinfurt (district), contains, Hörstel]
Generated description
Hörstel is a small town in North Rhine-Westphalia, Germany, known for its location near the Teutoburg Forest and the Dortmund–Ems Canal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hörstel Target entity description: Hörstel is a small town in North Rhine-Westphalia, Germany, known for its location near the Teutoburg Forest and the Dortmund–Ems Canal.
-
A.
Hörsel
Hörsel is a river in central Germany that flows through Thuringia and joins the Werra, contributing to the region’s drainage system.
-
B.
Hademstorf
Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
-
C.
Hohneck
Hohneck is one of the highest peaks in the Vosges Mountains of northeastern France, known for its panoramic views and popular hiking and skiing opportunities.
-
D.
Bernlohe
Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
-
E.
Geiselhöring
Geiselhöring is a small town in Lower Bavaria, Germany, known for its rural character and location within the Straubing-Bogen district.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75206354881908b148f2df3938513 |
completed | April 9, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e1550d6b4081909483c5dfa6e85671 |
completed | April 16, 2026, 9:30 p.m. |
| NEDg | Description generation | batch_69e17d3331788190a9ee03fc4c6ca191 |
completed | April 17, 2026, 12:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e1ff5b3d488190a545bee24381d01e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 8, 2026, 9:21 p.m.