Triple

T2294128
Position Surface form Disambiguated ID Type / Status
Subject Laura Arrillaga-Andreessen E51570 entity
Predicate hasGivenName P17 FINISHED
Object Laura E142585 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: Laura | Statement: [Laura Arrillaga-Andreessen, hasGivenName, Laura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura
Context triple: [Laura Arrillaga-Andreessen, hasGivenName, Laura]
  • A. Laura chosen
    Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • B. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • C. Lisa
    Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
  • D. Laurene
    Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
  • E. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5da667881909186adf23a2bd45b completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f2654e4819090dea196cf38652e completed March 9, 2026, 8:04 a.m.
Created at: March 4, 2026, 7:49 p.m.