Triple

T2934612
Position Surface form Disambiguated ID Type / Status
Subject Anya Taylor-Joy E79235 entity
Predicate notableWork P4 FINISHED
Object Emma E30843 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: Emma | Statement: [Anya Taylor-Joy, notableWork, Emma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma
Context triple: [Anya Taylor-Joy, notableWork, Emma]
  • A. Emma chosen
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • B. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • C. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • D. Amy
    Amy is a critically acclaimed 2015 documentary film about the life and career of British singer-songwriter Amy Winehouse.
  • E. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983c84688190aa7ed5b8091fb140 completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eed825108190b3db9728d0c95fd6 completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 2:56 p.m.