Triple

T6700396
Position Surface form Disambiguated ID Type / Status
Subject Marie Samuels E152863 entity
Predicate appearsInEpisode P795 FINISHED
Object Arkangel E564293 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: Arkangel | Statement: [Marie Samuels, appearsInEpisode, Arkangel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arkangel
Context triple: [Marie Samuels, appearsInEpisode, Arkangel]
  • A. Arkangel chosen
    Arkangel is an episode of the dystopian anthology series "Black Mirror" that explores parental overprotection through invasive surveillance technology implanted in a child.
  • B. Archangel
    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.
  • C. Archangel
    Archangel is a historical fiction collection by Andrea Barrett that intertwines science, war, and personal relationships in early 20th-century settings.
  • D. Archangel, Russia
    Archangel, Russia (Arkhangelsk) is a historic port city in northern Russia on the White Sea, long important as a maritime and trade gateway to the Arctic.
  • E. Vytegra
    Vytegra is a small town in northwestern Russia known as a regional center near Lake Onega and the White Sea–Baltic Canal.
  • 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_69c68807adbc8190b8632df42b39eda0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d0e4a1848190997520ddd7808cc6 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7c127288190a9917f482217a8df completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:05 p.m.