Triple

T6296723
Position Surface form Disambiguated ID Type / Status
Subject Mary Lynn Rajskub E141147 entity
Predicate performedIn P795 FINISHED
Object 2 Broke Girls E539593 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: 2 Broke Girls | Statement: [Mary Lynn Rajskub, performedIn, 2 Broke Girls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 2 Broke Girls
Context triple: [Mary Lynn Rajskub, performedIn, 2 Broke Girls]
  • A. 2 Broke Girls chosen
    2 Broke Girls is an American sitcom that follows the comedic misadventures of two financially struggling waitresses trying to start a cupcake business in Brooklyn.
  • B. New Girl in Town
    New Girl in Town is a 1957 Broadway musical adaptation of Eugene O’Neill’s play "Anna Christie," best known for its Tony-winning star turn by Gwen Verdon.
  • C. New Girl
    New Girl is an American sitcom that follows the quirky misadventures of Jess Day and her three male roommates in a Los Angeles loft.
  • D. Good Girls
    Good Girls is an American dark comedy-drama television series about three suburban mothers who turn to crime to solve their financial problems.
  • E. Scream Queens
    Scream Queens is a satirical horror-comedy television series that blends slasher tropes with dark humor and a college sorority setting.
  • 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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0643ac2b48190b2db036ce709e7ea completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5198e2c1c81909d39adffbdadcbdf completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:27 p.m.