Triple

T10882540
Position Surface form Disambiguated ID Type / Status
Subject UWWW E256960 entity
Predicate servesMetropolitanArea P82 FINISHED
Object Samara metropolitan area E67593 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: Samara metropolitan area | Statement: [UWWW, servesMetropolitanArea, Samara metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samara metropolitan area
Context triple: [UWWW, servesMetropolitanArea, Samara metropolitan area]
  • A. Samara chosen
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • B. Samara
    Samara is a city in northwestern Nigeria that forms part of the urban area of Zaria in Kaduna State.
  • C. Samara
    Samara is a design-focused housing and urban innovation company co-founded by Airbnb’s Joe Gebbia to explore new forms of living and community.
  • D. Moscow metropolitan area
    The Moscow metropolitan area is the large urban agglomeration centered on Russia’s capital city, encompassing Moscow and its surrounding suburbs and satellite towns.
  • E. Nizhny Novgorod
    Nizhny Novgorod is a major Russian city located at the confluence of the Volga and Oka rivers, known for its historic Kremlin, industrial significance, and role as a key cultural and economic center in the Volga 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751db24208190b3a7ed7eea118522 completed April 9, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3a91a3e1c819083ef144e7fd5603f completed April 18, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:21 p.m.