Triple
T15968776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spenge |
E387265
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Wallenbrück
Wallenbrück is a district or locality within the town of Spenge in North Rhine-Westphalia, Germany.
|
E1237482
|
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: Wallenbrück | Statement: [Spenge, hasSubdivision, Wallenbrück]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wallenbrück Context triple: [Spenge, hasSubdivision, Wallenbrück]
-
A.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
B.
Walzenhausen
Walzenhausen is a Swiss village and municipality in the canton of Appenzell Ausserrhoden, known for its scenic location above Lake Constance and views over the Rhine Valley.
-
C.
Wallenfels
Wallenfels is a small town in northern Bavaria, Germany, known for its scenic location in the Franconian Forest region.
-
D.
Hademstorf
Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
-
E.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
- 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: Wallenbrück Triple: [Spenge, hasSubdivision, Wallenbrück]
Generated description
Wallenbrück is a district or locality within the town of Spenge in North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wallenbrück Target entity description: Wallenbrück is a district or locality within the town of Spenge in North Rhine-Westphalia, Germany.
-
A.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
B.
Walzenhausen
Walzenhausen is a Swiss village and municipality in the canton of Appenzell Ausserrhoden, known for its scenic location above Lake Constance and views over the Rhine Valley.
-
C.
Wallenfels
Wallenfels is a small town in northern Bavaria, Germany, known for its scenic location in the Franconian Forest region.
-
D.
Hademstorf
Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
-
E.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c28f43988190aa06da8c356b9646 |
completed | May 10, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a00c31d79688190b09754074a0dbafb |
completed | May 10, 2026, 5:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c38569d081909f20b7cb32ceb714 |
completed | May 10, 2026, 5:42 p.m. |
Created at: April 10, 2026, 4:54 a.m.