Triple

T13870845
Position Surface form Disambiguated ID Type / Status
Subject Volmerange-les-Mines E333443 entity
Predicate hasNameInLanguage P15 FINISHED
Object Wolmeringen@de
Wolmeringen is the German name for the French commune Volmerange-les-Mines in the Moselle department of northeastern France.
 E1065396 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: Wolmeringen@de | Statement: [Volmerange-les-Mines, hasNameInLanguage, Wolmeringen@de]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wolmeringen@de
Context triple: [Volmerange-les-Mines, hasNameInLanguage, Wolmeringen@de]
  • A. Woringen
    Woringen is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
  • B. Worringen
    Worringen is a district in the northern part of Cologne, Germany, historically notable as the site of the 1288 Battle of Worringen.
  • C. Mössinger
    Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
  • D. Wolthusen
    Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
  • E. Werneuchen
    Werneuchen is a small town in the German state of Brandenburg, located northeast of Berlin and characterized by its rural surroundings and commuter links to the capital.
  • 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: Wolmeringen@de
Triple: [Volmerange-les-Mines, hasNameInLanguage, Wolmeringen@de]
Generated description
Wolmeringen is the German name for the French commune Volmerange-les-Mines in the Moselle department of northeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wolmeringen@de
Target entity description: Wolmeringen is the German name for the French commune Volmerange-les-Mines in the Moselle department of northeastern France.
  • A. Woringen
    Woringen is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
  • B. Worringen
    Worringen is a district in the northern part of Cologne, Germany, historically notable as the site of the 1288 Battle of Worringen.
  • C. Mössinger
    Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
  • D. Wolthusen
    Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
  • E. Werneuchen
    Werneuchen is a small town in the German state of Brandenburg, located northeast of Berlin and characterized by its rural surroundings and commuter links to the capital.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c638248190bbe5d19f7b88d0f9 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c107c20c81909dff0ca4a59fcc55 completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c20da9448190b3167b091bd39b94 completed May 3, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7c2cc63148190b9ca2828abe54286 completed May 3, 2026, 9:49 p.m.
Created at: April 9, 2026, 10:14 p.m.