Triple

T16710584
Position Surface form Disambiguated ID Type / Status
Subject DLA Piper E406094 entity
Predicate hasOfficeIn P1268 FINISHED
Object Brussels E10018 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: Brussels | Statement: [DLA Piper, hasOfficeIn, Brussels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brussels
Context triple: [DLA Piper, hasOfficeIn, Brussels]
  • A. Brussels
    Brussels is a small unincorporated community and town in Door County, Wisconsin, known for its strong Belgian-American heritage.
  • B. Brussels, Belgium chosen
    Brussels, Belgium is the capital city of Belgium and a major political center of Europe, hosting key institutions such as the European Union and numerous international organizations.
  • C. Antwerp
    Antwerp is a major Belgian port city on the River Scheldt, renowned as a global center for the diamond trade and its historic Flemish art and architecture.
  • D. Maastricht
    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.
  • E. Brussels metropolitan area
    The Brussels metropolitan area is the large urban region centered on Belgium’s capital, encompassing Brussels and its surrounding municipalities and commuter towns.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3865186b48190bb45a761f5cf1a83 completed April 18, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0123257b908190819986393cb35748 completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:20 a.m.