Triple

T9085668
Position Surface form Disambiguated ID Type / Status
Subject Felicia E217747 entity
Predicate hasOrigin P26 FINISHED
Object Latin language E5875 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: Latin language | Statement: [Felicia, hasOrigin, Latin language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Latin language
Context triple: [Felicia, hasOrigin, Latin language]
  • A. Latin chosen
    Latin is an ancient Italic language of the Roman Empire that profoundly shaped the vocabulary, grammar, and development of many European languages and scholarly traditions.
  • B. Latin I
    Latin I is an introductory course in the Latin language that typically covers basic grammar, vocabulary, and reading skills while introducing students to aspects of ancient Roman culture.
  • C. Latiano
    Latiano is a town and comune in the Apulia region of southern Italy, known for its historic center and agricultural traditions.
  • D. Vulgar Latin
    Vulgar Latin was the everyday, non-standard form of Latin spoken by common people in the Roman Empire, from which the Romance languages later evolved.
  • E. Old Latin
    Old Latin is the early form of the Latin language used in ancient Rome before the Classical period, preserved in archaic inscriptions and early literary texts.
  • 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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc960d0b008190b0e9e61fac45101d completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d017c893fc819087d18db2383b9bb4 completed April 3, 2026, 7:40 p.m.
Created at: March 30, 2026, 7:13 p.m.