Triple

T7464361
Position Surface form Disambiguated ID Type / Status
Subject Leer (district) E176335 entity
Predicate hasMunicipality P847 FINISHED
Object Jemgum
Jemgum is a small municipality in the East Frisian region of Lower Saxony in northwestern Germany, known for its rural landscape along the Ems River.
 E666412 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: Jemgum | Statement: [Leer (district), hasMunicipality, Jemgum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jemgum
Context triple: [Leer (district), hasMunicipality, Jemgum]
  • A. Junggumun
    Junggumun is a historical writing system used in Korea that incorporated Chinese characters to represent Korean grammatical elements and sounds.
  • B. Jangsaengpo
    Jangsaengpo is a coastal district in Ulsan, South Korea, historically known as a major whaling port and now a center for marine and whale-related tourism.
  • C. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • D. Gulgong
    Gulgong is a historic gold rush town in New South Wales, Australia, known for its well-preserved 19th-century streetscapes and heritage buildings.
  • E. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • 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: Jemgum
Triple: [Leer (district), hasMunicipality, Jemgum]
Generated description
Jemgum is a small municipality in the East Frisian region of Lower Saxony in northwestern Germany, known for its rural landscape along the Ems River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jemgum
Target entity description: Jemgum is a small municipality in the East Frisian region of Lower Saxony in northwestern Germany, known for its rural landscape along the Ems River.
  • A. Junggumun
    Junggumun is a historical writing system used in Korea that incorporated Chinese characters to represent Korean grammatical elements and sounds.
  • B. Jangsaengpo
    Jangsaengpo is a coastal district in Ulsan, South Korea, historically known as a major whaling port and now a center for marine and whale-related tourism.
  • C. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • D. Gulgong
    Gulgong is a historic gold rush town in New South Wales, Australia, known for its well-preserved 19th-century streetscapes and heritage buildings.
  • E. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d9d25c819087efc772b5b127fa completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8346adb3081908f049d8dcd623215 completed March 28, 2026, 8:04 p.m.
NEDg Description generation batch_69c835904be081908fa9317eb5568d82 completed March 28, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_69c83621b32c8190bd4b289b5f9f1764 completed March 28, 2026, 8:12 p.m.
Created at: March 27, 2026, 3:40 p.m.