Triple

T11776443
Position Surface form Disambiguated ID Type / Status
Subject To the Lighthouse E280030 entity
Predicate hasPart P35 FINISHED
Object The Window E547952 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: The Window | Statement: [To the Lighthouse, hasPart, The Window]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Window
Context triple: [To the Lighthouse, hasPart, The Window]
  • A. The Window chosen
    "The Window" is a 1949 American film noir thriller about a young boy who witnesses a murder but struggles to convince adults that the crime really occurred.
  • B. Ventanas
    Ventanas is a small city in Ecuador’s Los Ríos Province, known primarily for its agricultural surroundings and role as a local commercial center.
  • C. Through the Window
    "Through the Window" is a song featured on Eddie Vedder’s acoustic solo album "Higher Truth."
  • D. Through a Window
    Through a Window is a book by primatologist Jane Goodall that reflects on her decades of research and personal experiences with chimpanzees in the wild.
  • E. From a Window
    "From a Window" is a 1964 pop song written by John Lennon and Paul McCartney and recorded by Billy J. Kramer and the Dakotas.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a560bf548190afab3ad14f953a71 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090a95a908190a99e579e51cbeb4a completed April 28, 2026, 10:49 a.m.
Created at: April 8, 2026, 9:42 p.m.