Triple

T1980511
Position Surface form Disambiguated ID Type / Status
Subject Annabella E43014 entity
Predicate name P16 FINISHED
Object Annabella E43014 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: Annabella | Statement: [Annabella, name, Annabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annabella
Context triple: [Annabella, name, Annabella]
  • A. Annabella chosen
    Annabella was a French film actress of the 1930s and 1940s, known for her work in both European and Hollywood cinema.
  • B. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • C. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • D. Cecilia
    Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
  • E. Lenore
    "Lenore" is a melancholic poem by Edgar Allan Poe that explores themes of death, mourning, and idealized love through the lament for a lost woman.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb7c87bc081908ed179d1ca94fa3b completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae032bc30c8190a136a634580571d9 completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:37 p.m.