Triple

T22366111
Position Surface form Disambiguated ID Type / Status
Subject Ayesha Curry E552907 entity
Predicate hasTwitterUsername P2943 FINISHED
Object ayeshacurry NE NERFINISHED

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: ayeshacurry | Statement: [Ayesha Curry, hasTwitterUsername, ayeshacurry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ayeshacurry
Context triple: [Ayesha Curry, hasTwitterUsername, ayeshacurry]
  • A. Tuncurry
    Tuncurry is a coastal town in New South Wales, Australia, known for its beaches, lakes, and close connection to the twin town of Forster.
  • B. Curry chosen
    Curry is a common English-language surname borne by numerous notable individuals across fields such as religion, sports, and entertainment.
  • C. Meehni
    Meehni is one of the three iconic sandstone rock pillars known as the Three Sisters in the Blue Mountains of New South Wales, Australia.
  • D. Wazwan
    Wazwan is a lavish multi-course feast from Kashmir, renowned for its rich meat-based dishes and central role in weddings and special celebrations.
  • E. Sadya
    Sadya is a traditional Kerala feast served on a banana leaf, featuring a wide variety of vegetarian dishes, rice, and accompaniments typically prepared for festivals and special occasions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4affcc8190ba7c27d29062558d completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1580074dc819091305ac7017000d3 completed April 29, 2026, 12:59 a.m.
Created at: April 16, 2026, 8:44 p.m.