Triple

T12374212
Position Surface form Disambiguated ID Type / Status
Subject Perfect Couples E295080 entity
Predicate hasMainCharacter P1183 FINISHED
Object Julia E92860 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: Julia | Statement: [Perfect Couples, hasMainCharacter, Julia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julia
Context triple: [Perfect Couples, hasMainCharacter, Julia]
  • A. Julia chosen
    Julia is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • B. Julia
    Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
  • C. Julia
    "Julia" is a 1977 American drama film, based on Lillian Hellman’s memoir, that explores the intense lifelong friendship between a playwright and a woman involved in anti-fascist resistance before World War II.
  • D. gens Julia
    The gens Julia was one of ancient Rome’s most prominent patrician families, traditionally claiming descent from the Trojan hero Aeneas and including figures such as Julius Caesar and Augustus.
  • E. Rubinius
    Rubinius is an alternative Ruby implementation featuring a virtual machine and just-in-time compilation, designed for high performance and concurrency.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fa8ca7c8190b3f8e9c2ec23e837 completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac1e82c8190abb46ca5799e6680 completed May 2, 2026, 4:48 p.m.
Created at: April 8, 2026, 9:54 p.m.