Triple

T16147912
Position Surface form Disambiguated ID Type / Status
Subject Jeff Hephner E391834 entity
Predicate notableWork P4 FINISHED
Object Maid in Manhattan E341616 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: Maid in Manhattan | Statement: [Jeff Hephner, notableWork, Maid in Manhattan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maid in Manhattan
Context triple: [Jeff Hephner, notableWork, Maid in Manhattan]
  • A. Maid in Manhattan chosen
    Maid in Manhattan is a 2002 romantic comedy film in which Jennifer Lopez stars as a hotel maid who unexpectedly falls in love with a wealthy politician.
  • B. Manhattan Love Story
    Manhattan Love Story is a short-lived American romantic comedy television series that follows the dating lives and inner thoughts of a young couple in New York City.
  • C. First We Take Manhattan
    "First We Take Manhattan" is a darkly prophetic, synth-driven song by Leonard Cohen that blends political and apocalyptic imagery with his signature poetic lyricism.
  • D. Love in the Big City
    Love in the Big City is a popular Russian-Ukrainian romantic comedy film known for its lighthearted take on modern relationships and urban life.
  • E. Manhattan Transfer
    Manhattan Transfer is a modernist novel by John Dos Passos that portrays the fragmented, fast-paced life of early 20th-century New York City through a collage-like narrative style.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d9551e081908391061b092ff31b completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a7dc3481909f933acd72d6feff completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.