Triple

T317841
Position Surface form Disambiguated ID Type / Status
Subject Black Sea E7745 entity
Predicate receivesRiver P4359 FINISHED
Object Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
 E46936 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: Don | Statement: [Black Sea, receivesRiver, Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Don
Context triple: [Black Sea, receivesRiver, Don]
  • A. Dave
    Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
  • B. Donald
    Donald is the given name of Donald Trump, the 45th president of the United States and a prominent businessman and media personality.
  • C. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • D. Doug
    Doug is a common English masculine given name, typically used as a short form of Douglas.
  • E. John
    John is the given name of the English architect and dramatist John Vanbrugh, known for designing Blenheim Palace and Castle Howard.
  • 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: Don
Triple: [Black Sea, receivesRiver, Don]
Generated description
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Don
Target entity description: The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • A. Dave
    Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
  • B. Donald
    Donald is the given name of Donald Trump, the 45th president of the United States and a prominent businessman and media personality.
  • C. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • D. Doug
    Doug is a common English masculine given name, typically used as a short form of Douglas.
  • E. John
    John is the given name of the English architect and dramatist John Vanbrugh, known for designing Blenheim Palace and Castle Howard.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea67b7588190be394a56498758b6 completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3eca3d2f08190a0d4008cfb000f4f completed March 1, 2026, 7:37 a.m.
NEDg Description generation batch_69a3ee6e5d688190bc4e5cee8014ca4d completed March 1, 2026, 7:44 a.m.
NED2 Entity disambiguation (via description) batch_69a3ef1206148190a0cbc9ebfa943f06 completed March 1, 2026, 7:47 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.