Triple

T6632342
Position Surface form Disambiguated ID Type / Status
Subject Chernihiv E149955 entity
Predicate alternativeName P39 FINISHED
Object Чернігів
Чернігів — одне з найстаріших міст України, розташоване на півночі країни над Десною, відоме своєю давньоруською історією та архітектурними пам’ятками.
 E608580 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: Чернігів | Statement: [Chernihiv, alternativeName, Чернігів]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Чернігів
Context triple: [Chernihiv, alternativeName, Чернігів]
  • A. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • B. Vinnytsia
    Vinnytsia is a major city in central Ukraine known as an important administrative, economic, and cultural center on the Southern Bug River.
  • C. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • D. Ivano-Frankivsk
    Ivano-Frankivsk is a historic city in western Ukraine known as a cultural, economic, and administrative center of the Carpathian region.
  • E. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • 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: Чернігів
Triple: [Chernihiv, alternativeName, Чернігів]
Generated description
Чернігів — одне з найстаріших міст України, розташоване на півночі країни над Десною, відоме своєю давньоруською історією та архітектурними пам’ятками.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Чернігів
Target entity description: Чернігів — одне з найстаріших міст України, розташоване на півночі країни над Десною, відоме своєю давньоруською історією та архітектурними пам’ятками.
  • A. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • B. Vinnytsia
    Vinnytsia is a major city in central Ukraine known as an important administrative, economic, and cultural center on the Southern Bug River.
  • C. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • D. Ivano-Frankivsk
    Ivano-Frankivsk is a historic city in western Ukraine known as a cultural, economic, and administrative center of the Carpathian region.
  • E. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afc9138c81909d228ce4936d6b8b completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eeeaa67881908bef71c5fa61c599 completed March 27, 2026, 8:56 p.m.
NEDg Description generation batch_69c6f09ffdd481909418ae33d1683486 completed March 27, 2026, 9:03 p.m.
NED2 Entity disambiguation (via description) batch_69c6f159cbf08190a22d7488584b4580 completed March 27, 2026, 9:06 p.m.
Created at: March 27, 2026, 1:59 p.m.