Triple

T19890116
Position Surface form Disambiguated ID Type / Status
Subject Act Two of Chess E478005 entity
Predicate featuresCharacter P626 FINISHED
Object Molokov
Molokov is a shrewd Soviet official and KGB handler in the musical "Chess," known for his manipulative, politically driven control over the chess players.
 E1400142 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: Molokov | Statement: [Act Two of Chess, featuresCharacter, Molokov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molokov
Context triple: [Act Two of Chess, featuresCharacter, Molokov]
  • A. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • B. Khokhlov
    Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
  • C. Yuriev
    Yuriev is the historical name of the Ukrainian city now known as Bila Tserkva, an important regional center south of Kyiv.
  • D. Laptev
    Laptev is a Russian surname most notably associated with the 18th-century Arctic explorer Dmitry Laptev.
  • E. Malinovsky
    Malinovsky is a Russian surname most notably associated with Soviet military commander and Marshal of the Soviet Union Rodion Malinovsky.
  • 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: Molokov
Triple: [Act Two of Chess, featuresCharacter, Molokov]
Generated description
Molokov is a shrewd Soviet official and KGB handler in the musical "Chess," known for his manipulative, politically driven control over the chess players.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molokov
Target entity description: Molokov is a shrewd Soviet official and KGB handler in the musical "Chess," known for his manipulative, politically driven control over the chess players.
  • A. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • B. Khokhlov
    Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
  • C. Yuriev
    Yuriev is the historical name of the Ukrainian city now known as Bila Tserkva, an important regional center south of Kyiv.
  • D. Laptev
    Laptev is a Russian surname most notably associated with the 18th-century Arctic explorer Dmitry Laptev.
  • E. Malinovsky
    Malinovsky is a Russian surname most notably associated with Soviet military commander and Marshal of the Soviet Union Rodion Malinovsky.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6590ce9f48190a51c0e5ecc828a06 completed April 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07dbd3ac148190ba0067cacdf0f5d2 completed May 16, 2026, 2:52 a.m.
NEDg Description generation batch_6a07dccbcf788190bb03f396478b77f1 completed May 16, 2026, 2:56 a.m.
NED2 Entity disambiguation (via description) batch_6a07dd7f02d48190955d3b13a95b9c7e completed May 16, 2026, 2:59 a.m.
Created at: April 10, 2026, 1:52 p.m.