Triple

T4035228
Position Surface form Disambiguated ID Type / Status
Subject Ex Machina E83811 entity
Predicate mainCharacter P1183 FINISHED
Object Ava E183843 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: Ava | Statement: [Ex Machina, mainCharacter, Ava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ava
Context triple: [Ex Machina, mainCharacter, Ava]
  • A. Ava chosen
    Ava is a feminine given name most famously associated with American actress and Hollywood icon Ava Gardner.
  • B. Ava
    Ava was a prominent historical city and royal capital in Upper Burma (now Myanmar), serving as a major political and cultural center for several Burmese kingdoms.
  • C. Arielle
    Arielle is a given name shared by various individuals, including Arielle Zuckerberg, a venture capitalist and younger sister of Meta co-founder Mark Zuckerberg.
  • D. Lena
    Lena is a common feminine given name used in many languages, often derived from longer names such as Magdalena or Helena.
  • E. Lena
    Lena is an alternate given name of Lee Krasner, the influential American abstract expressionist painter and wife of Jackson Pollock.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb132f6c8190937acd35a6a5a9e4 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556415ebc8190a528c7e22dbf70df completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:36 p.m.