Triple

T16821481
Position Surface form Disambiguated ID Type / Status
Subject Mühlendamm Bridge E408902 entity
Predicate isInHistoricArea P19498 FINISHED
Object Berlin old town E1237364 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: Berlin old town | Statement: [Mühlendamm Bridge, isInHistoricArea, Berlin old town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berlin old town
Context triple: [Mühlendamm Bridge, isInHistoricArea, Berlin old town]
  • A. Berlin old town chosen
    Berlin old town is the historic core of Germany’s capital, characterized by its medieval street layout, landmark churches, and proximity to the River Spree.
  • B. Munich old town
    Munich old town is the historic city center of Munich, Germany, known for its medieval street layout, landmark churches, and major squares such as Marienplatz.
  • C. Berlin government district
    The Berlin government district is the central area of Germany’s capital that houses key federal institutions, including the Bundestag in the Reichstag building and the offices of the Chancellor.
  • D. Berlin
    Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • E. Berlin
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e6b59c8190ad562a80e71ce54c completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c79cdf9c8190aa20d536ca17ab81 completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 5:23 a.m.