Triple

T4249645
Position Surface form Disambiguated ID Type / Status
Subject Todor Zhivkov E95816 entity
Predicate givenName P17 FINISHED
Object Todor E270314 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: Todor | Statement: [Todor Zhivkov, givenName, Todor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Todor
Context triple: [Todor Zhivkov, givenName, Todor]
  • A. Georgi
    Georgi is a common Bulgarian male given name, widely used across Slavic countries and derived from the Greek name Georgios.
  • B. Alexander Toshev
    Alexander Toshev is a computer scientist known for his contributions to computer vision and deep learning, including influential work on object detection.
  • C. 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.
  • D. Mario Grigorov
    Mario Grigorov is a Bulgarian-born composer and pianist best known for his film scores and collaborations with director Lee Daniels.
  • E. Teodor chosen
    Teodor is a given name, commonly used in various European languages, that corresponds to the English name Theodore.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e9df10881908a2f039773f8afaa completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a87fdca481908bd2c80b10d0dd3d completed March 14, 2026, 6:27 p.m.
Created at: March 12, 2026, 11:06 p.m.