Triple

T9540588
Position Surface form Disambiguated ID Type / Status
Subject Straubing-Bogen E230145 entity
Predicate contains P35 FINISHED
Object Geiselhöring
Geiselhöring is a small town in Lower Bavaria, Germany, known for its rural character and location within the Straubing-Bogen district.
E821422 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: Geiselhöring | Statement: [Straubing-Bogen, contains, Geiselhöring]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geiselhöring
Context triple: [Straubing-Bogen, contains, Geiselhöring]
  • A. Hörsching
    Hörsching is a municipality in Upper Austria, best known for hosting Linz Airport and lying near the city of Linz.
  • B. Eschbach
    Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
  • C. Bergrheinfeld
    Bergrheinfeld is a municipality in the Schweinfurt district of northern Bavaria, Germany, known for its residential character and proximity to the industrial city of Schweinfurt.
  • D. Gerlosbach
    Gerlosbach is a mountain river in Tyrol, Austria, that flows through the Zillertal Alps before joining the Ziller.
  • E. Öhningen
    Öhningen is a municipality in southern Germany located on the western end of Lake Constance near the Swiss border, known for its scenic setting and prehistoric pile-dwelling sites.
  • 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: Geiselhöring
Triple: [Straubing-Bogen, contains, Geiselhöring]
Generated description
Geiselhöring is a small town in Lower Bavaria, Germany, known for its rural character and location within the Straubing-Bogen district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Geiselhöring
Target entity description: Geiselhöring is a small town in Lower Bavaria, Germany, known for its rural character and location within the Straubing-Bogen district.
  • A. Hörsching
    Hörsching is a municipality in Upper Austria, best known for hosting Linz Airport and lying near the city of Linz.
  • B. Eschbach
    Eschbach is a village and district of the town of Usingen in the Hochtaunus region of Hesse, Germany.
  • C. Bergrheinfeld
    Bergrheinfeld is a municipality in the Schweinfurt district of northern Bavaria, Germany, known for its residential character and proximity to the industrial city of Schweinfurt.
  • D. Gerlosbach
    Gerlosbach is a mountain river in Tyrol, Austria, that flows through the Zillertal Alps before joining the Ziller.
  • E. Öhningen
    Öhningen is a municipality in southern Germany located on the western end of Lake Constance near the Swiss border, known for its scenic setting and prehistoric pile-dwelling sites.
  • 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_69d1c3fa50388190bf2a1fbb50c6e0c0 completed April 5, 2026, 2:07 a.m.
NEDg Description generation batch_69d1c4eb7a0481908bbd72f6d28d4746 completed April 5, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69d1c5c0e6e88190bbf6eb379e6d1aa3 completed April 5, 2026, 2:15 a.m.
Created at: March 30, 2026, 8:01 p.m.