Triple

T4631561
Position Surface form Disambiguated ID Type / Status
Subject Arkhangelsk E101428 entity
Predicate hasAlternativeName P39 FINISHED
Object Archangel E42307 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: Archangel | Statement: [Arkhangelsk, hasAlternativeName, Archangel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Archangel
Context triple: [Arkhangelsk, hasAlternativeName, Archangel]
  • A. Archangel chosen
    Archangel is a historic Russian port city on the White Sea that served as a major northern gateway for European trade before the rise of St. Petersburg.
  • B. El Ángel
    El Ángel is a famous victory column and iconic symbol of Mexico City commemorating the country’s independence.
  • C. Angelus
    The Angelus is a traditional Catholic prayer recited three times daily in honor of the Incarnation, often accompanied by the ringing of church bells.
  • D. Archangel City
    Archangel City is an alternative name for the Russian port city of Arkhangelsk, a historic hub of Arctic trade and shipbuilding on the White Sea.
  • E. Erskyne
    Erskyne is an alternative spelling or variant form of the name Erskine, which is used as a surname and given name of Scottish origin.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a32d6408190962e60b9bce7560d completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfabeba3c8190b6515b99746f62a6 completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.