Triple

T4921533
Position Surface form Disambiguated ID Type / Status
Subject Bulgarian Navy (World War II) E110476 entity
Predicate usedPort P23954 FINISHED
Object Burgas E41854 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: Burgas | Statement: [Bulgarian Navy (World War II), usedPort, Burgas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burgas
Context triple: [Bulgarian Navy (World War II), usedPort, Burgas]
  • A. Burgas chosen
    Burgas is a major Bulgarian city and industrial center on the Black Sea coast, known for its large seaport and role as a key maritime and logistics hub in the region.
  • B. Dobrich
    Dobrich is a city in northeastern Bulgaria that serves as the administrative and economic center of the Dobrich Province in the historical region of Southern Dobruja.
  • C. Plovdiv
    Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
  • D. Pazardzhik
    Pazardzhik is a city in southern Bulgaria known as a regional economic and cultural center in the Upper Thracian Plain.
  • E. Blagoevgrad
    Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
  • 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_69bd4413f9908190afcff44d7929cc4c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ffc2ab08190992db2400562bcee completed March 20, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69be92394f048190b6c0c87eea844f56 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:30 p.m.