Triple

T10215692
Position Surface form Disambiguated ID Type / Status
Subject Havelland E242434 entity
Predicate containsMunicipality P852 FINISHED
Object Brieselang
Brieselang is a municipality in the Havelland district of Brandenburg, Germany, known for its residential character and proximity to Berlin.
E850650 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: Brieselang | Statement: [Havelland, containsMunicipality, Brieselang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brieselang
Context triple: [Havelland, containsMunicipality, Brieselang]
  • A. Schippenbeil
    Schippenbeil is the former German name for the town now known as Sępopol in northeastern Poland.
  • B. Breselenz
    Breselenz is a small village in Lower Saxony, Germany, best known as the birthplace of the mathematician Bernhard Riemann.
  • C. Langerak
    Langerak is a small village in the Dutch province of South Holland, known for its rural character and location along the Lek River.
  • D. Neerlangel
    Neerlangel is a small village in the Dutch province of North Brabant that forms part of the municipality of Oss.
  • E. Gailingen
    Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
  • 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: Brieselang
Triple: [Havelland, containsMunicipality, Brieselang]
Generated description
Brieselang is a municipality in the Havelland district of Brandenburg, Germany, known for its residential character and proximity to Berlin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brieselang
Target entity description: Brieselang is a municipality in the Havelland district of Brandenburg, Germany, known for its residential character and proximity to Berlin.
  • A. Schippenbeil
    Schippenbeil is the former German name for the town now known as Sępopol in northeastern Poland.
  • B. Breselenz
    Breselenz is a small village in Lower Saxony, Germany, best known as the birthplace of the mathematician Bernhard Riemann.
  • C. Langerak
    Langerak is a small village in the Dutch province of South Holland, known for its rural character and location along the Lek River.
  • D. Neerlangel
    Neerlangel is a small village in the Dutch province of North Brabant that forms part of the municipality of Oss.
  • E. Gailingen
    Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
  • 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.