Triple

T14501928
Position Surface form Disambiguated ID Type / Status
Subject Millie Rusk E340162 entity
Predicate alsoKnownAs P39 FINISHED
Object Molotov Girl E336621 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: Molotov Girl | Statement: [Millie Rusk, alsoKnownAs, Molotov Girl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molotov Girl
Context triple: [Millie Rusk, alsoKnownAs, Molotov Girl]
  • A. Molotov Girl chosen
    Molotov Girl is a rebellious, game-savvy character in the film "Free Guy," known for helping the protagonist uncover the truth about his virtual world.
  • B. Moscow Does Not Believe in Tears
    "Moscow Does Not Believe in Tears" is a 1980 Soviet romantic drama film that follows the lives of three women in Moscow over two decades, exploring themes of love, ambition, and social change, and won the Academy Award for Best Foreign Language Film.
  • C. Nevsky Express
    Nevsky Express is a high-speed Russian passenger train service that operates between Moscow and Saint Petersburg.
  • D. Foolish Fatherland
    Foolish Fatherland is the common English name for the early post-independence period in Colombia marked by political fragmentation and internal conflict between 1810 and 1816.
  • E. Molodyozhnaya
    Molodyozhnaya is a Moscow Metro station serving the western part of the city on one of its main radial lines.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e0f9048190a2d266cfa4f9dfb6 completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:21 a.m.