Triple

T14229430
Position Surface form Disambiguated ID Type / Status
Subject dba (Deutsche BA) E352711 entity
Predicate notableRoute P22 FINISHED
Object Munich–Hamburg E511258 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: Munich–Hamburg | Statement: [dba (Deutsche BA), notableRoute, Munich–Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munich–Hamburg
Context triple: [dba (Deutsche BA), notableRoute, Munich–Hamburg]
  • A. Hamburg–Munich chosen
    Hamburg–Munich is a major long-distance rail corridor in Germany connecting the northern port city of Hamburg with the southern metropolis of Munich.
  • B. Cologne–Munich
    Cologne–Munich is a major domestic air route in Germany connecting the cities of Cologne and Munich.
  • C. Frankfurt–Cologne
    Frankfurt–Cologne is a major high-speed rail corridor in Germany connecting the financial hub of Frankfurt with the Rhine metropolis of Cologne.
  • D. Vienna–Hamburg
    Vienna–Hamburg is an international overnight rail connection linking Austria’s capital with the major German port city of Hamburg.
  • E. Berlin–Munich
    Berlin–Munich is a major high-speed rail corridor in Germany connecting the capital with Bavaria’s largest city.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622b89fc8190af08dab9e1976759 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3251ec5881909fcebc9477d6a761 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:07 a.m.