Triple

T1381578
Position Surface form Disambiguated ID Type / Status
Subject Emden E29348 entity
Predicate hasTwinTown P919 FINISHED
Object Archangelsk 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: Archangelsk | Statement: [Emden, hasTwinTown, Archangelsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Archangelsk
Context triple: [Emden, hasTwinTown, Archangelsk]
  • 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. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • C. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • D. Novo-Arkhangelsk
    Novo-Arkhangelsk was the Russian colonial-era name for the settlement that later became the city of Sitka in present-day Alaska.
  • E. Krasnoyarsk
    Krasnoyarsk is a large industrial and cultural city in central Russia, situated on the Yenisei River and known as one of the key urban centers of Siberia.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c31b176c8190a896183140c5c8be completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5af961c8190aed3129dab0fecf3 completed March 8, 2026, 5:45 p.m.
Created at: March 1, 2026, 7:59 p.m.