Triple

T8182380
Position Surface form Disambiguated ID Type / Status
Subject Mack Swain E191093 entity
Predicate notableWork P4 FINISHED
Object Pay Day E342523 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: Pay Day | Statement: [Mack Swain, notableWork, Pay Day]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pay Day
Context triple: [Mack Swain, notableWork, Pay Day]
  • A. Paycheck
    Paycheck is a 2003 science fiction action thriller film, based on a Philip K. Dick short story, about an engineer who must piece together his erased memories to uncover a conspiracy.
  • B. Payday chosen
    Payday is a 1973 American drama film starring Rip Torn as a hard-living country singer whose self-destructive lifestyle unravels over the course of a few chaotic days.
  • C. Payday
    "Payday" is a song by the American rock band Culture, recognized as one of their notable musical works.
  • D. Payback
    Payback is a 1999 neo-noir crime film starring Mel Gibson as a vengeful thief seeking repayment after being double-crossed.
  • E. $40 a Day
    $40 a Day is a food and travel television show in which Rachael Ray explores different cities while demonstrating how to eat three meals and snacks on a budget of forty dollars.
  • 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c4db8748190aa785e0c70fac497 completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf8e8f0c819096f449760ce0d240 completed April 1, 2026, 6:47 a.m.
Created at: March 30, 2026, 5:40 p.m.