Triple

T5132579
Position Surface form Disambiguated ID Type / Status
Subject Ruhr area E115735 entity
Predicate containsCity P294 FINISHED
Object Moers
Moers is a city in western Germany’s North Rhine-Westphalia, known as a former coal-mining center on the western edge of the Ruhr industrial region.
 E495845 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: Moers | Statement: [Ruhr area, containsCity, Moers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moers
Context triple: [Ruhr area, containsCity, Moers]
  • A. Roermond
    Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
  • B. Münster
    Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
  • C. Xanten
    Xanten is a historic town in western Germany known for its well-preserved Roman archaeological park and medieval architecture.
  • D. Heerlen
    Heerlen is a city in the southeastern Netherlands known for its mining history and modernist architecture, located in the province of Limburg.
  • E. Wijchen
    Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
  • 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: Moers
Triple: [Ruhr area, containsCity, Moers]
Generated description
Moers is a city in western Germany’s North Rhine-Westphalia, known as a former coal-mining center on the western edge of the Ruhr industrial region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moers
Target entity description: Moers is a city in western Germany’s North Rhine-Westphalia, known as a former coal-mining center on the western edge of the Ruhr industrial region.
  • A. Roermond
    Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
  • B. Münster
    Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
  • C. Xanten
    Xanten is a historic town in western Germany known for its well-preserved Roman archaeological park and medieval architecture.
  • D. Heerlen
    Heerlen is a city in the southeastern Netherlands known for its mining history and modernist architecture, located in the province of Limburg.
  • E. Wijchen
    Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
  • 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_69bd444426bc819099ccd23f141e22aa completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd784b477c8190926daddb28a255af completed March 20, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec4c9a14881908a8bf2f73ebf56f7 completed March 21, 2026, 4:18 p.m.
NEDg Description generation batch_69bec562d0508190851b5a3307e9405b completed March 21, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69bec6478b848190bc09d7f6485681b4 completed March 21, 2026, 4:24 p.m.
Created at: March 20, 2026, 1:42 p.m.