Triple

T20324100
Position Surface form Disambiguated ID Type / Status
Subject Dan Duryea E492286 entity
Predicate notableWork P4 FINISHED
Object Too Late for Tears E1102516 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: Too Late for Tears | Statement: [Dan Duryea, notableWork, Too Late for Tears]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Too Late for Tears
Context triple: [Dan Duryea, notableWork, Too Late for Tears]
  • A. Too Late for Tears chosen
    Too Late for Tears is a 1949 film noir thriller about a housewife corrupted by a sudden windfall of illicit cash, noted for Lizabeth Scott’s hard-edged, morally ambiguous performance.
  • B. No Time for Tears
    "No Time for Tears" is a song by American singer Ashlee Simpson from her pop-rock album "Bittersweet World."
  • C. So Many Tears
    "So Many Tears" is a reflective and emotionally charged song by Tupac Shakur that explores themes of pain, loss, and inner turmoil.
  • D. There Will Be Tears
    "There Will Be Tears" is a pop and R&B-influenced song by British singer-songwriter and producer Mr Hudson, known for its emotional lyrics and polished, melodic production.
  • E. Hold Back the Tears
    "Hold Back the Tears" is a song by Neil Young featured on his 1977 album *American Stars 'n Bars*.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778e59508190bfd7a3ce44d56a93 completed April 20, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08612cc2c0819092d074fda6f0d995 completed May 16, 2026, 12:21 p.m.
Created at: April 16, 2026, 11:21 a.m.