Triple

T5893008
Position Surface form Disambiguated ID Type / Status
Subject Anastasia E131034 entity
Predicate followsCharacter P10688 FINISHED
Object Anya E563376 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: Anya | Statement: [Anastasia, followsCharacter, Anya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anya
Context triple: [Anastasia, followsCharacter, Anya]
  • A. Anya
    Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
  • B. Anya
    Anya is the given name of actress Anya Taylor-Joy, known for her roles in films like "The Witch" and the series "The Queen's Gambit."
  • C. Anya chosen
    Anya is the spirited, amnesiac young woman in the animated film "Anastasia" who embarks on a journey to discover whether she is the lost Russian Grand Duchess.
  • D. Natalya
    Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
  • E. Yelena
    Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b5c68481909fdcba428238c74d completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cbc676c8190bdac874391a608e8 completed March 23, 2026, 10:58 a.m.
Created at: March 22, 2026, 3:58 p.m.