Triple

T18714415
Position Surface form Disambiguated ID Type / Status
Subject Терек E457597 entity
Predicate hasTributary P415 FINISHED
Object Сунжа
Сунжа — это река на Северном Кавказе, протекающая через Чечню и Ингушетию и играющая важную роль в водной системе региона.
 E1338693 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: Сунжа | Statement: [Терек, hasTributary, Сунжа]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Сунжа
Context triple: [Терек, hasTributary, Сунжа]
  • A. Solnice
    Solnice is a small town in the Hradec Králové Region of the Czech Republic, known for its industrial facilities and proximity to the Orlické Mountains.
  • B. Saules
    Saules is a small municipality located in the Jura bernois region of the canton of Bern in Switzerland.
  • C. Surya
    Surya is the Hindu sun god revered as a major solar deity associated with light, power, and vitality.
  • D. Saha
    Saha is a small town in the Ambala district of the northern Indian state of Haryana, known primarily as a local commercial and transport hub for surrounding rural areas.
  • E. Saha
    Saha is a surname most notably associated with Indian astrophysicist Meghnad Saha, known for the Saha ionization equation in stellar astrophysics.
  • 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: Сунжа
Triple: [Терек, hasTributary, Сунжа]
Generated description
Сунжа — это река на Северном Кавказе, протекающая через Чечню и Ингушетию и играющая важную роль в водной системе региона.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Сунжа
Target entity description: Сунжа — это река на Северном Кавказе, протекающая через Чечню и Ингушетию и играющая важную роль в водной системе региона.
  • A. Solnice
    Solnice is a small town in the Hradec Králové Region of the Czech Republic, known for its industrial facilities and proximity to the Orlické Mountains.
  • B. Saules
    Saules is a small municipality located in the Jura bernois region of the canton of Bern in Switzerland.
  • C. Surya
    Surya is the Hindu sun god revered as a major solar deity associated with light, power, and vitality.
  • D. Saha
    Saha is a small town in the Ambala district of the northern Indian state of Haryana, known primarily as a local commercial and transport hub for surrounding rural areas.
  • E. Saha
    Saha is a surname most notably associated with Indian astrophysicist Meghnad Saha, known for the Saha ionization equation in stellar astrophysics.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56ab4ee6881908f19558937cbb078 completed April 19, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a052b413d348190b34e236d44fb541a completed May 14, 2026, 1:54 a.m.
NEDg Description generation batch_6a052c40cd04819096757952a275ddcf completed May 14, 2026, 1:58 a.m.
NED2 Entity disambiguation (via description) batch_6a052d1122ac819081c664d90d784a82 completed May 14, 2026, 2:01 a.m.
Created at: April 10, 2026, 11:50 a.m.