Triple

T715517
Position Surface form Disambiguated ID Type / Status
Subject Hesse E14304 entity
Predicate containsRegion P285 FINISHED
Object North Hesse
North Hesse is a region in the northern part of the German state of Hesse, centered around the city of Kassel and known for its forests, hills, and cultural heritage.
 E108856 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: North Hesse | Statement: [Hesse, containsRegion, North Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: North Hesse
Context triple: [Hesse, containsRegion, North Hesse]
  • A. Hesse
    Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
  • B. Sachse
    Sachse is a suburban city in the Dallas–Fort Worth metropolitan area of northeastern Texas.
  • C. Franconia
    Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
  • D. Upper Palatinate
    Upper Palatinate is a historical region in eastern Bavaria, Germany, known for its forests, rivers, and medieval towns near the Czech border.
  • E. Kellerwald
    Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
  • 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: North Hesse
Triple: [Hesse, containsRegion, North Hesse]
Generated description
North Hesse is a region in the northern part of the German state of Hesse, centered around the city of Kassel and known for its forests, hills, and cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: North Hesse
Target entity description: North Hesse is a region in the northern part of the German state of Hesse, centered around the city of Kassel and known for its forests, hills, and cultural heritage.
  • A. Hesse
    Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
  • B. Sachse
    Sachse is a suburban city in the Dallas–Fort Worth metropolitan area of northeastern Texas.
  • C. Franconia
    Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
  • D. Upper Palatinate
    Upper Palatinate is a historical region in eastern Bavaria, Germany, known for its forests, rivers, and medieval towns near the Czech border.
  • E. Kellerwald
    Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a574b4d881908b6d0be386081efd completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf4b62b08190bc8d5978595ce60b completed March 4, 2026, 6:20 a.m.
NEDg Description generation batch_69a7d19fd2e481908218d532888418d9 completed March 4, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69a7d2308ed88190b223fe6d2fbb5662 completed March 4, 2026, 6:33 a.m.
Created at: March 1, 2026, 7:37 p.m.