Triple

T11299788
Position Surface form Disambiguated ID Type / Status
Subject A Blonde in Love E267552 entity
Predicate castMember P1668 FINISHED
Object Jiří Hrubý
Jiří Hrubý is an actor known for appearing in the classic Czech New Wave film "A Blonde in Love."
E931595 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: Jiří Hrubý | Statement: [A Blonde in Love, castMember, Jiří Hrubý]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiří Hrubý
Context triple: [A Blonde in Love, castMember, Jiří Hrubý]
  • A. Miroslav Ondříček
    Miroslav Ondříček was a renowned Czech cinematographer known for his collaborations with director Miloš Forman on films such as "Amadeus" and "Ragtime."
  • B. Jiří Paroubek
    Jiří Paroubek is a Czech politician who served as Prime Minister of the Czech Republic and a leading figure in the country’s social democratic movement.
  • C. Jaromír Hanzlík
    Jaromír Hanzlík is a Czech film and television actor best known for his roles in popular Czechoslovak movies and TV series from the 1960s onward.
  • D. Viktor Pospíšil
    Viktor Pospíšil is a conductor and music director known for his leadership at the Staatsoper Stuttgart.
  • E. Miroslav Holeček
    Miroslav Holeček is a Czech academic and university administrator who has served as rector of the University of West Bohemia.
  • 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: Jiří Hrubý
Triple: [A Blonde in Love, castMember, Jiří Hrubý]
Generated description
Jiří Hrubý is an actor known for appearing in the classic Czech New Wave film "A Blonde in Love."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jiří Hrubý
Target entity description: Jiří Hrubý is an actor known for appearing in the classic Czech New Wave film "A Blonde in Love."
  • A. Miroslav Ondříček
    Miroslav Ondříček was a renowned Czech cinematographer known for his collaborations with director Miloš Forman on films such as "Amadeus" and "Ragtime."
  • B. Jiří Paroubek
    Jiří Paroubek is a Czech politician who served as Prime Minister of the Czech Republic and a leading figure in the country’s social democratic movement.
  • C. Jaromír Hanzlík
    Jaromír Hanzlík is a Czech film and television actor best known for his roles in popular Czechoslovak movies and TV series from the 1960s onward.
  • D. Viktor Pospíšil
    Viktor Pospíšil is a conductor and music director known for his leadership at the Staatsoper Stuttgart.
  • E. Miroslav Holeček
    Miroslav Holeček is a Czech academic and university administrator who has served as rector of the University of West Bohemia.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9a4aad4819097384e1b591be2e3 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e684ba7e0481908235e3e45f8902e6 completed April 20, 2026, 7:55 p.m.
NEDg Description generation batch_69e699599cb88190919e077a757c527c completed April 20, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_69e6a9716b908190add15ed69c8b676a completed April 20, 2026, 10:32 p.m.
Created at: April 8, 2026, 9:32 p.m.