Triple

T18621411
Position Surface form Disambiguated ID Type / Status
Subject Baku oil fields E455157 entity
Predicate near P350 FINISHED
Object Baku city NE NERFINISHED

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 city | Statement: [Baku oil fields, near, Baku city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baku city
Context triple: [Baku oil fields, near, Baku city]
  • 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. Shamkir
    Shamkir is a town in western Azerbaijan known as a regional center with historical significance and a growing agricultural and industrial economy.
  • D. Shamakhi
    Shamakhi is a historic city in Azerbaijan known for its long-standing Jewish community and cultural significance in the region.
  • E. Akçaabat
    Akçaabat is a coastal town and district in Turkey’s Trabzon Province on the Black Sea, known for its historic architecture and distinctive local cuisine.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54f0146f48190a872032db6e660c6 completed April 19, 2026, 9:54 p.m.
Created at: April 10, 2026, 11:46 a.m.