Triple

T4088286
Position Surface form Disambiguated ID Type / Status
Subject Twente E87641 entity
Predicate hasMunicipality P847 FINISHED
Object Losser
Losser is a municipality in the eastern Netherlands, located in the province of Overijssel near the German border.
 E413748 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: Losser | Statement: [Twente, hasMunicipality, Losser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Losser
Context triple: [Twente, hasMunicipality, Losser]
  • A. Lorens
    Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
  • B. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • C. Shriever
    Shriever is a surname, a variant spelling of "Shriver," borne by various individuals of English-speaking origin.
  • D. Leisen
    Leisen is a surname most notably associated with Mitchell Leisen, a prominent American film director and art director of Hollywood’s classic era.
  • E. Lester
    Lester is the central character in the 2016 puzzle-platform video game "Mekazoo" (also known as "Makers" in some regions), around whom the game's story and gameplay revolve.
  • 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: Losser
Triple: [Twente, hasMunicipality, Losser]
Generated description
Losser is a municipality in the eastern Netherlands, located in the province of Overijssel near the German border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Losser
Target entity description: Losser is a municipality in the eastern Netherlands, located in the province of Overijssel near the German border.
  • A. Lorens
    Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
  • B. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • C. Shriever
    Shriever is a surname, a variant spelling of "Shriver," borne by various individuals of English-speaking origin.
  • D. Leisen
    Leisen is a surname most notably associated with Mitchell Leisen, a prominent American film director and art director of Hollywood’s classic era.
  • E. Lester
    Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
  • 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_69aed94425148190be337845d56fac22 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefca899008190b5ada98bdb79639f completed March 9, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b6335c4819093538f261a5093b3 completed March 14, 2026, 2:06 p.m.
NEDg Description generation batch_69b56f249fa08190b14793f298ed160c completed March 14, 2026, 2:22 p.m.
NED2 Entity disambiguation (via description) batch_69b56f91065c8190bd6767249109d715 completed March 14, 2026, 2:24 p.m.
Created at: March 9, 2026, 3:39 p.m.