Triple

T34280297
Position Surface form Disambiguated ID Type / Status
Subject Tower 185 E879572 entity
Predicate rankingInCountryByHeight P185686 FINISHED
Object one of the tallest office towers in Germany LITERAL 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: one of the tallest office towers in Germany | Statement: [Tower 185, rankingInCountryByHeight, one of the tallest office towers in Germany]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankingInCountryByHeight
Context triple: [Tower 185, rankingInCountryByHeight, one of the tallest office towers in Germany]
  • A. countryRankByHeight
    Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
  • B. countryRankByHeightAtCompletion
    Indicates the position of a country in an ordered list based on the height of something (typically a structure or project) at the time it was completed.
  • C. regionRankByHeight
    Indicates the relative ordering of regions based on their height or elevation.
  • D. rankByHeightWorld
    Indicates an ordering of entities based on their relative height compared to all others in the world.
  • E. rankingInChinaByHeight
    Indicates the position or order of an entity in a height-based ranking specifically within the context of China.
  • F. None of above. chosen

Provenance (4 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_69f349b5f6648190b9420d94a4cd16e0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7c33d59808190b647989a093f3488 completed May 3, 2026, 9:50 p.m.
PD Predicate disambiguation batch_69f7c1b6e7a881908deb96bedb2713f4 completed May 3, 2026, 9:44 p.m.
PDg Predicate description generation batch_69f7c29cf36481908e472d4dcb5573b9 completed May 3, 2026, 9:48 p.m.
Created at: May 1, 2026, 1:57 a.m.