Triple
T14679878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lüdenscheid |
E344748
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object |
RSV Lüdenscheid
RSV Lüdenscheid is a German sports club based in the town of Lüdenscheid, known for organizing and promoting local athletic activities and competitions.
|
E1113630
|
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: RSV Lüdenscheid | Statement: [Lüdenscheid, hasSportsClub, RSV Lüdenscheid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RSV Lüdenscheid Context triple: [Lüdenscheid, hasSportsClub, RSV Lüdenscheid]
-
A.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
B.
Ritterhude
Ritterhude is a small town in northern Germany’s Lower Saxony, situated just northwest of Bremen.
-
C.
Rheinhausen
Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
-
D.
Raesfeld
Raesfeld is a municipality in western Germany’s North Rhine-Westphalia, known for its historic moated castle and rural surroundings.
-
E.
Rheinsberg
Rheinsberg is a small historic town in Brandenburg, Germany, best known for its picturesque lakeside palace that served as a residence for Prussian royalty.
- 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: RSV Lüdenscheid Triple: [Lüdenscheid, hasSportsClub, RSV Lüdenscheid]
Generated description
RSV Lüdenscheid is a German sports club based in the town of Lüdenscheid, known for organizing and promoting local athletic activities and competitions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RSV Lüdenscheid Target entity description: RSV Lüdenscheid is a German sports club based in the town of Lüdenscheid, known for organizing and promoting local athletic activities and competitions.
-
A.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
B.
Ritterhude
Ritterhude is a small town in northern Germany’s Lower Saxony, situated just northwest of Bremen.
-
C.
Rheinhausen
Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
-
D.
Raesfeld
Raesfeld is a municipality in western Germany’s North Rhine-Westphalia, known for its historic moated castle and rural surroundings.
-
E.
Rheinsberg
Rheinsberg is a small historic town in Brandenburg, Germany, best known for its picturesque lakeside palace that served as a residence for Prussian royalty.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb5692284819090f775be8e478522 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde180ff0c8190a8b7c7804e36c3f8 |
completed | May 8, 2026, 1:13 p.m. |
| NEDg | Description generation | batch_69fde447189881909b4b0dc654a05e0d |
completed | May 8, 2026, 1:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fde53290a48190b3701472bb4e3d63 |
completed | May 8, 2026, 1:29 p.m. |
Created at: April 10, 2026, 1:27 a.m.