Triple

T1312143
Position Surface form Disambiguated ID Type / Status
Subject Ruhr Pocket E28014 entity
Predicate significantPlace P1098 FINISHED
Object Menden
Menden is a town in North Rhine-Westphalia, Germany, known for its location in the Sauerland region and its involvement in World War II events such as the Ruhr Pocket.
E149798 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: Menden | Statement: [Ruhr Pocket, significantPlace, Menden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Menden
Context triple: [Ruhr Pocket, significantPlace, Menden]
  • A. Holly Springs
    Holly Springs is a suburban town in North Carolina known for its rapid growth, family-friendly communities, and proximity to the Research Triangle’s technology and research hubs.
  • B. Trinityville
    Trinityville is a rural community located in the parish of St. Thomas in eastern Jamaica.
  • C. Kenly
    Kenly is a small town in North Carolina known for its rural character and location along major transportation routes.
  • D. Kanesville
    Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
  • E. Johnson City
    Johnson City is a mid-sized city in northeastern Tennessee known as part of the Tri-Cities region and a hub for education, healthcare, and outdoor recreation.
  • 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: Menden
Triple: [Ruhr Pocket, significantPlace, Menden]
Generated description
Menden is a town in North Rhine-Westphalia, Germany, known for its location in the Sauerland region and its involvement in World War II events such as the Ruhr Pocket.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Menden
Target entity description: Menden is a town in North Rhine-Westphalia, Germany, known for its location in the Sauerland region and its involvement in World War II events such as the Ruhr Pocket.
  • A. Holly Springs
    Holly Springs is a suburban town in North Carolina known for its rapid growth, family-friendly communities, and proximity to the Research Triangle’s technology and research hubs.
  • B. Trinityville
    Trinityville is a rural community located in the parish of St. Thomas in eastern Jamaica.
  • C. Kenly
    Kenly is a small town in North Carolina known for its rural character and location along major transportation routes.
  • D. Kanesville
    Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
  • E. Johnson City
    Johnson City is a mid-sized city in northeastern Tennessee known as part of the Tri-Cities region and a hub for education, healthcare, and outdoor recreation.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1572b1c8190ab978198c2d655c8 completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbaeeece08190a805a2f037e709ce completed March 7, 2026, 11:55 p.m.
NEDg Description generation batch_69acbb74a0e48190b2018b16363afea1 completed March 7, 2026, 11:57 p.m.
NED2 Entity disambiguation (via description) batch_69acbbcd8c1c8190b58680d7a1ecd982 completed March 7, 2026, 11:59 p.m.
Created at: March 1, 2026, 7:55 p.m.