Triple

T12992182
Position Surface form Disambiguated ID Type / Status
Subject Michael Apted E321931 entity
Predicate directed P7373 FINISHED
Object Gorky Park E368098 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: Gorky Park | Statement: [Michael Apted, directed, Gorky Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gorky Park
Context triple: [Michael Apted, directed, Gorky Park]
  • A. Gorky Park
    Gorky Park is a famous central Moscow park known for its recreational facilities, cultural events, and scenic riverside location.
  • B. Gorky Park chosen
    Gorky Park is a 1983 crime thriller film, based on Martin Cruz Smith’s novel, about a Soviet detective investigating a triple murder in Moscow.
  • C. Taganana
    Taganana is a historic coastal village on Tenerife in Spain’s Canary Islands, known for its dramatic cliffs, traditional architecture, and location within the Anaga mountain range.
  • D. Vecherniy Kvartal
    Vecherniy Kvartal is a popular Ukrainian comedy and satirical TV show known for its sketches, political humor, and live performances.
  • E. 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.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e7765788190a9503ef055bc30ca completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0fca5e4819086b010fdd1813419 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:44 p.m.