Triple

T2500338
Position Surface form Disambiguated ID Type / Status
Subject Olivia E52448 entity
Predicate hasDiminutive P456 FINISHED
Object Livvy E52448 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: Livvy | Statement: [Olivia, hasDiminutive, Livvy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Livvy
Context triple: [Olivia, hasDiminutive, Livvy]
  • A. Lily
    Lily is a feminine given name of English origin commonly associated with the lily flower and symbolizing purity and beauty.
  • B. Lily
    Lily is a pivotal character in the psychological thriller film "Black Swan," serving as a seductive and enigmatic rival whose presence intensifies the protagonist's descent into paranoia and self-destruction.
  • C. Olivia chosen
    Olivia is a feminine given name of Latin origin meaning "olive tree," widely used in English-speaking countries and popularized by literature and modern media.
  • D. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • E. Libby
    Libby is a surname most notably associated with Willard F. Libby, the American chemist who developed radiocarbon dating and won the Nobel Prize in Chemistry.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1b144a481909b1f8d96742a92e7 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1fa0e26481908e383a6d44b3f3d5 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:46 p.m.