Triple

T13107508
Position Surface form Disambiguated ID Type / Status
Subject Kelly Price E310881 entity
Predicate notableWork P4 FINISHED
Object Mirror Mirror E890601 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: Mirror Mirror | Statement: [Kelly Price, notableWork, Mirror Mirror]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mirror Mirror
Context triple: [Kelly Price, notableWork, Mirror Mirror]
  • A. Mirror Mirror chosen
    Mirror Mirror is a 2012 fantasy comedy film that offers a whimsical, visually stylized retelling of the Snow White fairy tale.
  • B. Mirror, Mirror
    "Mirror, Mirror" is a classic Star Trek: The Original Series episode that introduces the iconic "mirror universe," depicting darker alternate versions of the Enterprise crew.
  • C. Mirrors
    "Mirrors" is a 2013 pop and R&B ballad by Justin Timberlake, known for its reflective lyrics about lasting love and its expansive, multi-part production.
  • D. Mirror
    "Mirror" is a reflective, introspective hip-hop/R&B song by Lil Wayne featuring Bruno Mars, known for its emotional lyrics and soulful hook.
  • E. Mirror
    Mirror is a 1975 Russian art film by director Andrei Tarkovsky that blends poetry, memory, and dreamlike imagery in a non-linear meditation on personal and collective history.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817ce07881909ec552bf861ac175 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27a325c8190a5c0f1a582340078 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:05 p.m.