Triple

T16418103
Position Surface form Disambiguated ID Type / Status
Subject Julius E398739 entity
Predicate hasCognate P2525 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: [Julius, hasCognate, Julia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julia
Context triple: [Julius, hasCognate, Julia]
  • A. 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.
  • B. Julia chosen
    Julia is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • 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. Jula language
    Jula language is a Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328798a488190a5fad01c3c95584c completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c6ca1bc8190a6c4f675ec8e3a53 completed May 10, 2026, 8:06 a.m.
Created at: April 10, 2026, 5:09 a.m.