Triple

T19995786
Position Surface form Disambiguated ID Type / Status
Subject Margraten E494188 entity
Predicate locatedNear P294 FINISHED
Object Maastricht NE NERFINISHED

How this triple was built (2 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: Maastricht | Statement: [Margraten, locatedNear, Maastricht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maastricht
Context triple: [Margraten, locatedNear, Maastricht]
  • A. Maastricht chosen
    Maastricht is a historic city in the southeastern Netherlands known for its medieval architecture, vibrant cultural scene, and as the birthplace of the Maastricht Treaty that founded the European Union.
  • B. Brussels
    Brussels is a small unincorporated community and town in Door County, Wisconsin, known for its strong Belgian-American heritage.
  • C. Bruges
    Bruges is a historic Belgian city renowned for its well-preserved medieval architecture, picturesque canals, and rich artistic heritage.
  • D. Bruges
    Bruges is a commune in southwestern France, located near the city of Bordeaux in the Gironde department.
  • E. Aachen
    Aachen is a historic German city near the borders with Belgium and the Netherlands, renowned for its medieval cathedral, role as a coronation site for Holy Roman Emperors, and significance in both World Wars.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65fe3fb288190a935c334e8a5d54e completed April 20, 2026, 5:18 p.m.
Created at: April 11, 2026, 3:32 p.m.