Triple

T4443349
Position Surface form Disambiguated ID Type / Status
Subject Random E96222 entity
Predicate programmingLanguage P1592 FINISHED
Object Julia E17648 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: [Random, programmingLanguage, Julia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julia
Context triple: [Random, programmingLanguage, Julia]
  • A. 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.
  • B. Julia
    Julia is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • C. Julia chosen
    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.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355b052688190a0d8e5912f82151c completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b672251b408190b3883a6895c154d7 completed March 15, 2026, 8:47 a.m.
Created at: March 12, 2026, 11:32 p.m.