Triple

T13846846
Position Surface form Disambiguated ID Type / Status
Subject Novodvinsk E332827 entity
Predicate locatedEastOf P4240 FINISHED
Object Arkhangelsk E101428 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: Arkhangelsk | Statement: [Novodvinsk, locatedEastOf, Arkhangelsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arkhangelsk
Context triple: [Novodvinsk, locatedEastOf, Arkhangelsk]
  • A. Arkhangelsk chosen
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • B. Archangelskoye
    Archangelskoye is a historic estate and former aristocratic residence near Moscow, Russia, known for its neoclassical palace, landscaped park, and role as a cultural and political retreat.
  • C. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • D. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • E. Tomsk
    Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b2a9788190b164760adec64ef6 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcd08c21a48190b4077d5acb4ab658 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:13 p.m.