Triple

T13286239
Position Surface form Disambiguated ID Type / Status
Subject Return to Me E316451 entity
Predicate screenwriter P2831 FINISHED
Object Don Lake NE NERFINISHED

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: Don Lake | Statement: [Return to Me, screenwriter, Don Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Lake
Context triple: [Return to Me, screenwriter, Don Lake]
  • A. Don Lake chosen
    Don Lake is a Canadian actor, writer, and comedian known for his character roles in film and television and frequent collaborations with director Christopher Guest.
  • B. Park Lake
    Park Lake is a recreational lake and park area in Santa Rosa, New Mexico, popular for swimming, picnicking, and outdoor activities.
  • C. Walker Lake
    Walker Lake is a large natural desert lake in western Nevada known for its shrinking water levels and importance as a habitat for migratory birds and native fish.
  • D. Inspiration Lake
    Inspiration Lake is a man-made recreational lake and landscaped park near Hong Kong Disneyland, popular for walking, jogging, and family outings.
  • E. Roy Lake
    Roy Lake is a freshwater lake and popular recreational area in northeastern South Dakota known for fishing, boating, and camping.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990759ebc8190a9487a59e37a69e2 completed April 11, 2026, 12:06 a.m.
Created at: April 9, 2026, 9:27 p.m.