Triple

T6994346
Position Surface form Disambiguated ID Type / Status
Subject Andrew Miano E162169 entity
Predicate notableWork P4 FINISHED
Object Miss Stevens E602477 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: Miss Stevens | Statement: [Andrew Miano, notableWork, Miss Stevens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miss Stevens
Context triple: [Andrew Miano, notableWork, Miss Stevens]
  • A. Miss Stevens chosen
    Miss Stevens is a 2016 indie drama film in which Timothée Chalamet gives an early acclaimed performance as a troubled high school student on a road trip with his teacher to a drama competition.
  • B. Ms. Weiss
    Ms. Weiss is a social worker character in the film "Precious," known for her pivotal role in supporting the abused teenage protagonist.
  • C. Ms. Kelly
    Ms. Kelly is the second solo studio album by American singer Kelly Rowland, showcasing her R&B sound following her success with Destiny's Child.
  • D. Miss Rose White
    Miss Rose White is a 1992 television drama film about a Holocaust survivor rebuilding her life in New York, noted for Kyra Sedgwick’s acclaimed lead performance.
  • E. Ms. Teets
    Ms. Teets is the central character of the story "Good Vibes," around whom the main events and themes revolve.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbeaa88c8190a49f8504c1793e1f completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a1adec88190a769ec7af0fa7b51 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.