Triple

T14016808
Position Surface form Disambiguated ID Type / Status
Subject Samara Embankment E337224 entity
Predicate locatedIn P40 FINISHED
Object Samara 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 | Statement: [Samara Embankment, locatedIn, Samara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samara
Context triple: [Samara Embankment, locatedIn, Samara]
  • A. 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.
  • B. Samara chosen
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • C. Samara
    Samara is a city in northwestern Nigeria that forms part of the urban area of Zaria in Kaduna State.
  • D. Lesosibirsk
    Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
  • E. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f396b648190927e5718c3bb6511 completed April 14, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d0008dc819088fcfbfe3640af47 completed May 8, 2026, 1:31 a.m.
Created at: April 9, 2026, 10:19 p.m.