Triple

T4895246
Position Surface form Disambiguated ID Type / Status
Subject Branobel E109659 entity
Predicate headquartersLocation P62 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: [Branobel, headquartersLocation, Baku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baku
Context triple: [Branobel, headquartersLocation, 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. Kizlyar
    Kizlyar is a town in the Republic of Dagestan, Russia, known historically as a frontier settlement and trading center in the North Caucasus region.
  • C. Ashgabat
    Ashgabat is the largest city and political, economic, and cultural center of Turkmenistan, known for its grand marble architecture and monumental cityscape.
  • D. 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.
  • E. 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.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e27cdf48190bb9bd13bd25b887e completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81b9ab4c81909173686a76d32a88 completed March 21, 2026, 11:32 a.m.
Created at: March 20, 2026, 1:28 p.m.