Triple

T592356
Position Surface form Disambiguated ID Type / Status
Subject Alexander the Great E17303 entity
Predicate spouse P13 FINISHED
Object Roxana E66871 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: Roxana | Statement: [Alexander the Great, spouse, Roxana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roxana
Context triple: [Alexander the Great, spouse, Roxana]
  • A. Roxana chosen
    Roxana is a feminine given name of Persian origin, historically associated with figures such as the wife of Alexander the Great and later borne by various notable women.
  • B. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • C. Caterina
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Diana
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bbcaf5c81908de4e27096d3da13 completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a577891a148190ae1364191f7f63bb completed March 2, 2026, 11:42 a.m.
Created at: March 1, 2026, 7:33 p.m.