Triple

T14659322
Position Surface form Disambiguated ID Type / Status
Subject Date Night E344193 entity
Predicate starring P1507 FINISHED
Object Tina Fey E11671 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: Tina Fey | Statement: [Date Night, starring, Tina Fey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tina Fey
Context triple: [Date Night, starring, Tina Fey]
  • A. Tina Fey chosen
    Tina Fey is an American comedian, writer, actress, and producer best known for her work on "Saturday Night Live" and creating the acclaimed sitcom "30 Rock."
  • B. Amy Poehler
    Amy Poehler is an American comedian, actress, writer, and producer best known for her work on "Saturday Night Live" and for starring as Leslie Knope on the sitcom "Parks and Recreation."
  • C. Maya Rudolph
    Maya Rudolph is an American actress and comedian known for her work on "Saturday Night Live" and in numerous film and animated voice roles.
  • D. Kristen Wiig
    Kristen Wiig is an American comedian, actress, and writer best known for her work on Saturday Night Live and films such as Bridesmaids.
  • E. Amy Schumer
    Amy Schumer is an American stand-up comedian, actress, and writer known for her sharp, self-deprecating humor and work on projects like "Inside Amy Schumer" and "Trainwreck."
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51b6a248190a44050c0e0ec2d16 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe387f28688190b9d20f1e2bbc0ddc completed May 8, 2026, 7:24 p.m.
Created at: April 10, 2026, 1:27 a.m.