Triple

T16633849
Position Surface form Disambiguated ID Type / Status
Subject Christopher Lambert E404146 entity
Predicate awardReceivedFor P107 FINISHED
Object Subway E634882 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: Subway | Statement: [Christopher Lambert, awardReceivedFor, Subway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subway
Context triple: [Christopher Lambert, awardReceivedFor, Subway]
  • A. Subway chosen
    Subway is a 1985 French crime-comedy film directed by Luc Besson, known for its stylish depiction of Paris’s underground subculture and featuring Isabelle Adjani and Christopher Lambert.
  • B. Subway
    Subway is a global fast-food restaurant franchise best known for its made-to-order submarine sandwiches and salads.
  • C. IND Subway
    IND Subway is the city-owned Independent Subway System in New York City, built in the early 20th century to compete with private transit operators and now forming a core part of the modern NYC Subway.
  • D. Subway Wind
    "Subway Wind" is a poem by Claude McKay that vividly captures the gritty, restless atmosphere of New York City’s underground transit system.
  • E. Subway Stories
    Subway Stories is a 1997 HBO anthology film composed of short vignettes set in the New York City subway, exploring the intersecting lives and experiences of diverse passengers.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e7d4a48190a9b4a14ecbb2a14b completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084b984d081909f76ef874431ff40 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:17 a.m.