Triple

T6530325
Position Surface form Disambiguated ID Type / Status
Subject WWE Tough Enough E152213 entity
Predicate mentor P3665 FINISHED
Object Lita E600076 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: Lita | Statement: [WWE Tough Enough, mentor, Lita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lita
Context triple: [WWE Tough Enough, mentor, Lita]
  • A. Lita chosen
    Lita is a WWE Hall of Famer and pioneering women's professional wrestler known for her high-flying style and influential role in the evolution of women's wrestling.
  • B. Lita Grey
    Lita Grey was an American actress best known for her early silent-film work and her highly publicized, scandalous marriage to Charlie Chaplin as a teenager.
  • C. Leona Vicario
    Leona Vicario was a prominent Mexican independence heroine, journalist, and supporter of the insurgent cause against Spanish rule in the early 19th century.
  • D. Lana Banks
    Lana Banks is a notable individual who has gained recognition under the surname Banks, though specific widely known public details about her are limited.
  • E. Lana
    Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
  • 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_69c688048ec8819093a47f7d332e12ec completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6adac53b0819097fece48a75cc48f completed March 27, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d52ca9988190addfdae6d7b53a6e completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:46 p.m.