Triple

T9745841
Position Surface form Disambiguated ID Type / Status
Subject Main River region E236304 entity
Predicate containsCity P294 FINISHED
Object Marktheidenfeld
Marktheidenfeld is a small town in Lower Franconia, Bavaria, Germany, known for its location on the River Main and its historic old town.
 E907339 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: Marktheidenfeld | Statement: [Main River region, containsCity, Marktheidenfeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marktheidenfeld
Context triple: [Main River region, containsCity, Marktheidenfeld]
  • A. Erstfeld
    Erstfeld is a municipality in the Swiss canton of Uri, situated in a mountainous valley that serves as an important transport corridor through the Alps.
  • B. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • C. Lülsfeld
    Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • D. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • E. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • 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: Marktheidenfeld
Triple: [Main River region, containsCity, Marktheidenfeld]
Generated description
Marktheidenfeld is a small town in Lower Franconia, Bavaria, Germany, known for its location on the River Main and its historic old town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marktheidenfeld
Target entity description: Marktheidenfeld is a small town in Lower Franconia, Bavaria, Germany, known for its location on the River Main and its historic old town.
  • A. Erstfeld
    Erstfeld is a municipality in the Swiss canton of Uri, situated in a mountainous valley that serves as an important transport corridor through the Alps.
  • B. Hademstorf
    Hademstorf is a small municipality in Lower Saxony, Germany, situated in the Heidekreis district.
  • C. Lülsfeld
    Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • D. Breckerfeld
    Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
  • E. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f65ad788190b68d731b6f516d93 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4415b7f848190a9fc8b08824f0b9b completed April 19, 2026, 2:43 a.m.
NEDg Description generation batch_69e448f697a88190ae711c72ae0c0c3b completed April 19, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_69e4510dc55081908f89aab15726b2a8 completed April 19, 2026, 3:50 a.m.
Created at: March 30, 2026, 8:23 p.m.