Triple

T14443658
Position Surface form Disambiguated ID Type / Status
Subject Sebastian Tapijn E358147 entity
Predicate placeOfActivity P1527 FINISHED
Object Maastricht E168527 NE FINISHED

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: [Sebastian Tapijn, placeOfActivity, Maastricht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maastricht
Context triple: [Sebastian Tapijn, placeOfActivity, 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. Bruges
    Bruges is a historic Belgian city renowned for its well-preserved medieval architecture, picturesque canals, and rich artistic heritage.
  • C. Bruges
    Bruges is a commune in southwestern France, located near the city of Bordeaux in the Gironde department.
  • D. 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.
  • E. Hasselt
    Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de915d28ec81909e72124e9dd67bfb completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7ed3ec8190b97128733419845b completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:19 a.m.