Triple

T10776539
Position Surface form Disambiguated ID Type / Status
Subject Sleeper E254210 entity
Predicate followedBy P78 FINISHED
Object Love and Death E254211 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: Love and Death | Statement: [Sleeper, followedBy, Love and Death]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Love and Death
Context triple: [Sleeper, followedBy, Love and Death]
  • A. Love and Death chosen
    Love and Death is a 1975 satirical comedy film by Woody Allen that parodies Russian literature and philosophy through absurdist humor and existential musings.
  • B. Love and Death
    Love and Death is a symbolic 19th-century painting by British artist George Frederic Watts that explores the confrontation between human affection and mortality.
  • C. Love & Death
    Love & Death is a reflective work by theologian Forrest Church that explores mortality, meaning, and the power of love in the face of death.
  • D. The Crimes of Love
    The Crimes of Love is a collection of short stories by the Marquis de Sade that blends gothic melodrama with philosophical explorations of desire, morality, and cruelty.
  • E. Fatelessness
    Fatelessness is a semi-autobiographical novel by Nobel laureate Imre Kertész that portrays a Hungarian Jewish boy’s harrowing experiences in Nazi concentration camps and his struggle to comprehend them afterward.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7329d8c908190bddad40685133ea1 completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69de238ff88881908676d38dca041cb4 completed April 14, 2026, 11:22 a.m.
Created at: April 8, 2026, 9:16 p.m.