Triple

T9540741
Position Surface form Disambiguated ID Type / Status
Subject Kelheim (district) E230148 entity
Predicate containsMunicipality P852 FINISHED
Object Elsendorf
Elsendorf is a small municipality in the Lower Bavarian region of Germany.
E805673 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: Elsendorf | Statement: [Kelheim (district), containsMunicipality, Elsendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elsendorf
Context triple: [Kelheim (district), containsMunicipality, Elsendorf]
  • A. Iveland
    Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
  • B. Arensburg
    Arensburg is the former German name for Kuressaare, a historic town and seaside resort on Saaremaa Island in Estonia.
  • C. Froland
    Froland is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and historical ties to the mathematician Niels Henrik Abel.
  • D. Elmora
    Elmora is a residential neighborhood within the city of Elizabeth in Union County, New Jersey.
  • E. Oldisleben
    Oldisleben is a small town in the German state of Thuringia, known for its location along the Unstrut River and its historical rural character.
  • 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: Elsendorf
Triple: [Kelheim (district), containsMunicipality, Elsendorf]
Generated description
Elsendorf is a small municipality in the Lower Bavarian region of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elsendorf
Target entity description: Elsendorf is a small municipality in the Lower Bavarian region of Germany.
  • A. Iveland
    Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
  • B. Arensburg
    Arensburg is the former German name for Kuressaare, a historic town and seaside resort on Saaremaa Island in Estonia.
  • C. Froland
    Froland is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and historical ties to the mathematician Niels Henrik Abel.
  • D. Elmora
    Elmora is a residential neighborhood within the city of Elizabeth in Union County, New Jersey.
  • E. Oldisleben
    Oldisleben is a small town in the German state of Thuringia, known for its location along the Unstrut River and its historical rural character.
  • 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_69d14c6538b08190a9f81304214a876d completed April 4, 2026, 5:37 p.m.
NEDg Description generation batch_69d14d44b7f08190b66fecb315b37535 completed April 4, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69d14e0823e881908ed723d20f14789b completed April 4, 2026, 5:44 p.m.
Created at: March 30, 2026, 8:01 p.m.