Triple

T9768454
Position Surface form Disambiguated ID Type / Status
Subject Gheorghe E237057 entity
Predicate hasRelatedName P3889 FINISHED
Object Georgi E400091 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: Georgi | Statement: [Gheorghe, hasRelatedName, Georgi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgi
Context triple: [Gheorghe, hasRelatedName, Georgi]
  • A. Georgi chosen
    Georgi is a common Bulgarian male given name, widely used across Slavic countries and derived from the Greek name Georgios.
  • B. Georgy Georgiu
    Georgy Georgiu is an actor known for his role in the Soviet adventure-comedy film "Gentlemen of Fortune."
  • C. Dimitar
    Dimitar is a masculine given name of Slavic origin, commonly used in Bulgaria and other Eastern European countries.
  • D. Theodore Svetoslav
    Theodore Svetoslav was a medieval Bulgarian tsar who restored and strengthened the Second Bulgarian Empire in the early 14th century through military successes and internal consolidation.
  • E. Najden Gerov
    Najden Gerov was a prominent 19th-century Bulgarian educator, linguist, and public figure known for his major contributions to Bulgarian language studies and national cultural awakening.
  • 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0a2da648190836916a45d2998d7 completed April 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bd05f2588190ab413d26342aa70f completed April 5, 2026, 1:38 a.m.
Created at: March 30, 2026, 8:25 p.m.