Triple

T11489392
Position Surface form Disambiguated ID Type / Status
Subject Liliana E272364 entity
Predicate hasVariant P455 FINISHED
Object Lilianna E272364 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: Lilianna | Statement: [Liliana, hasVariant, Lilianna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lilianna
Context triple: [Liliana, hasVariant, Lilianna]
  • A. Liliana chosen
    Liliana is a feminine given name, often considered a more elaborate or romantic variant of Lily, used in various cultures around the world.
  • B. Éliante
    Éliante is a thoughtful and moderate young woman in Molière’s play *Le Misanthrope*, often seen as the voice of reason and a foil to the more extreme characters.
  • C. Janna Ordonia
    Janna Ordonia is a mischievous, troublemaking human girl in *Star vs. the Forces of Evil*, known for her love of the occult, pranks, and deadpan humor.
  • D. Edlyne
    Edlyne is the middle name of Thomas Edlyne Tomlins, an English legal writer and editor of the 19th century.
  • E. Rainelle
    Rainelle is a small town located in western Greenbrier County, West Virginia, historically tied to the lumber industry and the surrounding Appalachian region.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85a20df608190992543b4d7006f8a completed April 10, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6046ec5108190a0294cc86e1b60cc completed April 20, 2026, 10:48 a.m.
Created at: April 8, 2026, 9:36 p.m.