Triple

T19598286
Position Surface form Disambiguated ID Type / Status
Subject Max Rubner Institute E470402 entity
Predicate hasBranch P35 FINISHED
Object Hamburg 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: Hamburg | Statement: [Max Rubner Institute, hasBranch, Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg
Context triple: [Max Rubner Institute, hasBranch, Hamburg]
  • A. Hamburg chosen
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • B. Bremen
    Bremen is a small village in Fairfield County, Ohio, known for its historic charm and tight-knit rural community.
  • C. Bremen
    Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
  • D. Bremen
    Bremen is a small city in western Georgia, United States, known as a regional hub along major transportation routes and as part of the Atlanta metropolitan area’s outer region.
  • E. Bremen
    Bremen is a powerful and legendary druid from Terry Brooks' Shannara series, known for forging the Sword of Shannara and opposing the Warlock Lord.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407c52c081908704d3a4dd6e853b completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.