Triple

T3109638
Position Surface form Disambiguated ID Type / Status
Subject Maritsa E64918 entity
Predicate flowsThroughCity P10456 FINISHED
Object Plovdiv E191700 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: Plovdiv | Statement: [Maritsa, flowsThroughCity, Plovdiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plovdiv
Context triple: [Maritsa, flowsThroughCity, Plovdiv]
  • A. Plovdiv chosen
    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.
  • B. Burgas
    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.
  • C. 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.
  • D. Tarnovo
    Tarnovo, often called Veliko Tarnovo, is a historic Bulgarian city famed as a medieval capital and cultural stronghold, known for its dramatic hillside setting and well-preserved architectural heritage.
  • E. Varna
    Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada2a0ab2481908db50738ec3ad0fb completed March 8, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b203902a6881909b20589fad629640 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.