Triple

T11843361
Position Surface form Disambiguated ID Type / Status
Subject Diddenuewen E281708 entity
Predicate cityLocatedInDepartment P101811 FINISHED
Object Moselle E93471 NE FINISHED

How this triple was built (3 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: Moselle | Statement: [Diddenuewen, cityLocatedInDepartment, Moselle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moselle
Context triple: [Diddenuewen, cityLocatedInDepartment, Moselle]
  • A. Moselle chosen
    Moselle is a department in northeastern France, bordering Germany and Luxembourg, known for its strategic location, industrial history, and mixed French-German cultural heritage.
  • B. Moselle River
    The Moselle River is a major European waterway flowing through France, Luxembourg, and Germany, renowned for its scenic valleys and wine-producing regions.
  • C. Saar River
    The Saar River is a major river in northeastern France and western Germany that flows through the industrial region of Saarland before joining the Moselle.
  • D. Merzig
    Merzig is a town in the Saarland region of western Germany, near the borders with France and Luxembourg.
  • E. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: cityLocatedInDepartment
Context triple: [Diddenuewen, cityLocatedInDepartment, Moselle]
  • A. capitalOfDepartment
    Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
  • B. prefectureOfDepartment
    Indicates that a given prefecture administers or is the capital authority of a specified department.
  • C. geographicDirectionFromDepartmentCapital
    Indicates that one location lies in a specified geographic direction relative to the capital city of a given administrative department.
  • D. hasPopulationRankInDepartment
    Indicates the relative position of an entity’s population size compared to other entities within the same department.
  • E. capitalOfCommune
    Indicates that one place serves as the administrative capital or chief town of a given commune.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65a597c8190b09f57463b279afc completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f49cbc6808819094a73b505907e2ef completed May 1, 2026, 12:29 p.m.
PD Predicate disambiguation batch_69d8a254a57481908a1e6ad97919c416 completed April 10, 2026, 7:10 a.m.
PDg Predicate description generation batch_69d8a43cc0c881909fed7cd759fe90b1 completed April 10, 2026, 7:18 a.m.
Created at: April 8, 2026, 9:43 p.m.