Triple

T9254411
Position Surface form Disambiguated ID Type / Status
Subject T2 Trainspotting E222404 entity
Predicate productionCompany P490 FINISHED
Object DNA Films E258397 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: DNA Films | Statement: [T2 Trainspotting, productionCompany, DNA Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DNA Films
Context triple: [T2 Trainspotting, productionCompany, DNA Films]
  • A. DNA Films chosen
    DNA Films is a British film production company known for producing notable movies such as "28 Days Later" and other critically acclaimed features.
  • B. DNA
    DNA (deoxyribonucleic acid) is the hereditary molecule in almost all living organisms, encoding genetic instructions that guide development, function, and reproduction.
  • C. DNA
    DNA is the unicameral legislative body and main law-making institution of the Republic of Suriname.
  • D. DNA
    DNA is a major social-democratic political party in Norway, historically one of the country’s dominant governing parties.
  • E. DNAA
    DNAA is the ICAO airport code for Nnamdi Azikiwe International Airport, the main international gateway serving Abuja, Nigeria’s capital city.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd06b1f6bc81908115e22652d0c85e completed April 1, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0780c9efc81909470e7c64e23ffed completed April 4, 2026, 2:31 a.m.
Created at: March 30, 2026, 7:31 p.m.