Triple

T7310534
Position Surface form Disambiguated ID Type / Status
Subject Bhikaji Cama E168078 entity
Predicate location P40 FINISHED
Object Stuttgart, Germany E36930 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: Stuttgart, Germany | Statement: [Bhikaji Cama, location, Stuttgart, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stuttgart, Germany
Context triple: [Bhikaji Cama, location, Stuttgart, Germany]
  • A. Weinheim, Germany
    Weinheim, Germany is a town in the state of Baden-Württemberg known for its historic old town, twin castles, and role as a regional economic and publishing center.
  • B. Stuttgart chosen
    Stuttgart is a major city in southwestern Germany known as an important industrial, cultural, and economic center, particularly famous for its automotive industry and surrounding wine-growing region.
  • C. Rastatt, Germany
    Rastatt, Germany is a historic town in the state of Baden-Württemberg known for its Baroque palaces and role as a regional administrative and industrial center.
  • D. Göppingen, Germany
    Göppingen is a town in the German state of Baden-Württemberg known as an industrial and technology hub, including being home to the remote-access software company TeamViewer.
  • E. Ingolstadt
    Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
  • 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_69c6888d8e3c81909db79714903baf31 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebff866081909916796d1b72aee8 completed March 27, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e56b4178819087341903a168440b completed March 28, 2026, 2:27 p.m.
Created at: March 27, 2026, 3:01 p.m.