Triple

T932005
Position Surface form Disambiguated ID Type / Status
Subject Robert Nobel E20112 entity
Predicate placeOfActivity P1527 FINISHED
Object Baku E81696 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: Baku | Statement: [Robert Nobel, placeOfActivity, Baku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baku
Context triple: [Robert Nobel, placeOfActivity, Baku]
  • A. Baku chosen
    Baku is the capital and largest city of Azerbaijan, known for its rich blend of Islamic heritage and modern architecture on the shores of the Caspian Sea.
  • B. Ashgabat
    Ashgabat is the largest city and political, economic, and cultural center of Turkmenistan, known for its grand marble architecture and monumental cityscape.
  • C. Batumi
    Batumi is a major Black Sea resort city in southwestern Georgia known for its beaches, modern skyline, and role as a regional economic and cultural hub.
  • D. Baku Governorate
    Baku Governorate was an administrative division of the Russian Empire and later the early Soviet state, centered on the city of Baku in the South Caucasus region.
  • E. Tbilisi
    Tbilisi is the largest city and cultural, political, and economic center of Georgia, located on the banks of the Kura River in the South Caucasus.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b34c457c819085cbfa0c798cb4c6 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16fbe454819085020fc245c959ed completed March 7, 2026, 12:15 p.m.
Created at: March 1, 2026, 7:40 p.m.