Triple

T12512697
Position Surface form Disambiguated ID Type / Status
Subject Kirovsky District, Leningrad Oblast E299118 entity
Predicate hasUrbanTypeSettlement P40854 FINISHED
Object Mga
Mga is an urban-type settlement in Russia’s Leningrad Oblast, known primarily as a railway junction east of Saint Petersburg.
 E987887 NE FINISHED

How this triple was built (4 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: Mga | Statement: [Kirovsky District, Leningrad Oblast, hasUrbanTypeSettlement, Mga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mga
Context triple: [Kirovsky District, Leningrad Oblast, hasUrbanTypeSettlement, Mga]
  • A. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • B. MGA
    MGA is the IATA airport code for Augusto C. Sandino International Airport, the main international gateway serving Managua, Nicaragua.
  • C. MGA
    MGA is the official ISO 4217 currency code for the Malagasy ariary, the national currency of Madagascar.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. Ma
    Ma is a fictional character appearing in Enid Blyton’s children’s adventure novel "The Circus of Adventure."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mga
Triple: [Kirovsky District, Leningrad Oblast, hasUrbanTypeSettlement, Mga]
Generated description
Mga is an urban-type settlement in Russia’s Leningrad Oblast, known primarily as a railway junction east of Saint Petersburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mga
Target entity description: Mga is an urban-type settlement in Russia’s Leningrad Oblast, known primarily as a railway junction east of Saint Petersburg.
  • A. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • B. MGA
    MGA is the IATA airport code for Augusto C. Sandino International Airport, the main international gateway serving Managua, Nicaragua.
  • C. MGA
    MGA is the official ISO 4217 currency code for the Malagasy ariary, the national currency of Madagascar.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. Ma
    Ma is a fictional character appearing in Enid Blyton’s children’s adventure novel "The Circus of Adventure."
  • F. None of above. chosen

Provenance (5 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541e752c8190bf12d2b5a37b53df completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bbba5fc819082a4171a5a77183a completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64d15a97c81909046190f0d0fd986 completed May 2, 2026, 7:14 p.m.
NED2 Entity disambiguation (via description) batch_69f64e6d311c8190b851b89e394165d0 completed May 2, 2026, 7:20 p.m.
Created at: April 8, 2026, 9:57 p.m.