Triple

T5148601
Position Surface form Disambiguated ID Type / Status
Subject Romulus, My Father E116135 entity
Predicate character P662 FINISHED
Object Christina E75185 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: Christina | Statement: [Romulus, My Father, character, Christina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christina
Context triple: [Romulus, My Father, character, Christina]
  • A. Christina chosen
    Christina is a feminine given name widely used in many cultures, often associated with notable figures in entertainment, arts, and public life.
  • B. Christiane
    Christiane is the given name of Christiane Nüsslein-Volhard, the Nobel Prize–winning German developmental biologist known for her pioneering work on genetic control of embryonic development.
  • C. Krista
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • D. Christina Bailey
    Christina Bailey is a mysterious and doomed young woman whose frantic plea for help sets off the dark, twisting events of the classic 1955 film noir "Kiss Me Deadly."
  • E. Christa
    Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
  • 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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd78b17028819080568715df8c13eb completed March 20, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfff6e8c8190883fc981fca95f48 completed March 21, 2026, 5:06 p.m.
Created at: March 20, 2026, 1:43 p.m.