Triple

T8683399
Position Surface form Disambiguated ID Type / Status
Subject Egrisi E206092 entity
Predicate hasAlternativeName P39 FINISHED
Object Lazika E509005 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: Lazika | Statement: [Egrisi, hasAlternativeName, Lazika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lazika
Context triple: [Egrisi, hasAlternativeName, Lazika]
  • A. Lazikē chosen
    Lazikē is the historical region on the eastern coast of the Black Sea, in what is now western Georgia, that served as the homeland of the Laz people and a strategic frontier between the Byzantine and Sasanian empires.
  • B. Sama Chakeva
    Sama Chakeva is a traditional folk festival of the Mithila region celebrating the bond between brothers and sisters through songs, rituals, and decorative clay idols of birds.
  • C. Sevdaliza
    Sevdaliza is an Iranian-Dutch singer, songwriter, and producer known for her experimental blend of electronic, trip-hop, and avant-pop music paired with highly conceptual visual art.
  • D. Lela
    Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
  • E. Lujza
    Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
  • 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_69ca835379688190aa06b9d98e684d58 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4ae9da3c8190866e24970a7aeba3 completed March 31, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3c3c74c81908cd9e881d5963492 completed April 2, 2026, 10:54 p.m.
Created at: March 30, 2026, 6:32 p.m.