Triple
T13114062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mecklenburgische Seenplatte (district) |
E311047
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Feldberg
Feldberg is a small town in northeastern Germany known for its scenic lakes and forests within the Mecklenburg Lake District.
|
E1021593
|
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: Feldberg | Statement: [Mecklenburgische Seenplatte (district), contains, Feldberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feldberg Context triple: [Mecklenburgische Seenplatte (district), contains, Feldberg]
-
A.
Feldberg
Feldberg is the tallest mountain in Germany’s Black Forest region, known for its scenic landscapes and popular hiking and skiing opportunities.
-
B.
Eibenberg
Eibenberg is a small locality that forms one of the subdivisions of the municipality of Burkhardtsdorf in Saxony, Germany.
-
C.
Felsberg
Felsberg is a settlement located in the historical region of Westphalia in western Germany.
-
D.
Kleiner Feldberg
Kleiner Feldberg is a secondary summit in the Taunus mountain range in Hesse, Germany, known for its elevation and nearby scientific and meteorological facilities.
-
E.
Erzhausen
Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
- 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: Feldberg Triple: [Mecklenburgische Seenplatte (district), contains, Feldberg]
Generated description
Feldberg is a small town in northeastern Germany known for its scenic lakes and forests within the Mecklenburg Lake District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Feldberg Target entity description: Feldberg is a small town in northeastern Germany known for its scenic lakes and forests within the Mecklenburg Lake District.
-
A.
Feldberg
Feldberg is the tallest mountain in Germany’s Black Forest region, known for its scenic landscapes and popular hiking and skiing opportunities.
-
B.
Eibenberg
Eibenberg is a small locality that forms one of the subdivisions of the municipality of Burkhardtsdorf in Saxony, Germany.
-
C.
Felsberg
Felsberg is a settlement located in the historical region of Westphalia in western Germany.
-
D.
Kleiner Feldberg
Kleiner Feldberg is a secondary summit in the Taunus mountain range in Hesse, Germany, known for its elevation and nearby scientific and meteorological facilities.
-
E.
Erzhausen
Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817f8ee8819084078b4bec5e4f18 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e28105c481908781775ba489c296 |
completed | May 3, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69f6e33f44208190881bee81c2a41850 |
completed | May 3, 2026, 5:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e407dd988190b928b8931985a815 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 9, 2026, 9:06 p.m.