Triple
T9540668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regen (district) |
E230146
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ruhmannsfelden
Ruhmannsfelden is a small market town in the Bavarian Forest region of southeastern Germany.
|
E896395
|
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: Ruhmannsfelden | Statement: [Regen (district), contains, Ruhmannsfelden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruhmannsfelden Context triple: [Regen (district), contains, Ruhmannsfelden]
-
A.
Hakenfelde
Hakenfelde is a locality in the Berlin borough of Spandau, known for its residential areas, green spaces, and proximity to the Havel River.
-
B.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
C.
Hellefeld
Hellefeld is a village and district within the town of Sundern in the Hochsauerland region of North Rhine-Westphalia, Germany.
-
D.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
-
E.
Erstfeld
Erstfeld is a municipality in the Swiss canton of Uri, situated in a mountainous valley that serves as an important transport corridor through the Alps.
- 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: Ruhmannsfelden Triple: [Regen (district), contains, Ruhmannsfelden]
Generated description
Ruhmannsfelden is a small market town in the Bavarian Forest region of southeastern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruhmannsfelden Target entity description: Ruhmannsfelden is a small market town in the Bavarian Forest region of southeastern Germany.
-
A.
Hakenfelde
Hakenfelde is a locality in the Berlin borough of Spandau, known for its residential areas, green spaces, and proximity to the Havel River.
-
B.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
C.
Hellefeld
Hellefeld is a village and district within the town of Sundern in the Hochsauerland region of North Rhine-Westphalia, Germany.
-
D.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
-
E.
Erstfeld
Erstfeld is a municipality in the Swiss canton of Uri, situated in a mountainous valley that serves as an important transport corridor through the Alps.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d62cce008190ae269bbd289625a0 |
completed | April 18, 2026, 12:54 a.m. |
| NEDg | Description generation | batch_69e2fab58f588190ae2d33f32e71333b |
completed | April 18, 2026, 3:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e317809c0881909e793db965194014 |
completed | April 18, 2026, 5:32 a.m. |
Created at: March 30, 2026, 8:01 p.m.