Triple

T10215703
Position Surface form Disambiguated ID Type / Status
Subject Havelland E242434 entity
Predicate containsMunicipality P852 FINISHED
Object Märkisch Luch
Märkisch Luch is a rural municipality in the Havelland district of the German state of Brandenburg.
E850657 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: Märkisch Luch | Statement: [Havelland, containsMunicipality, Märkisch Luch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Märkisch Luch
Context triple: [Havelland, containsMunicipality, Märkisch Luch]
  • A. Rübeland
    Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
  • B. Schwanfeld
    Schwanfeld is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and historical roots.
  • C. Badenburg
    Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
  • D. Havelland
    Havelland is a rural district in western Brandenburg, Germany, known for its river landscapes along the Havel, historic towns, and agricultural character.
  • E. Löwenberger Land
    Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
  • 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: Märkisch Luch
Triple: [Havelland, containsMunicipality, Märkisch Luch]
Generated description
Märkisch Luch is a rural municipality in the Havelland district of the German state of Brandenburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Märkisch Luch
Target entity description: Märkisch Luch is a rural municipality in the Havelland district of the German state of Brandenburg.
  • A. Rübeland
    Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
  • B. Schwanfeld
    Schwanfeld is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and historical roots.
  • C. Badenburg
    Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
  • D. Havelland
    Havelland is a rural district in western Brandenburg, Germany, known for its river landscapes along the Havel, historic towns, and agricultural character.
  • E. Löwenberger Land
    Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa2894d0819095704449ecc2db6c completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6a804e8748190b4ebcfa9a0bb889f completed April 8, 2026, 7:09 p.m.
NEDg Description generation batch_69d6d0003434819093e3f82a556db79c completed April 8, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69d6df3c8f748190923db41ef1a9a03a completed April 8, 2026, 11:05 p.m.
Created at: April 6, 2026, 11:05 a.m.