Triple

T11299782
Position Surface form Disambiguated ID Type / Status
Subject A Blonde in Love E267552 entity
Predicate mainCharacter P1183 FINISHED
Object Andula
Andula is the naive yet emotionally complex young woman at the heart of Miloš Forman’s Czech New Wave film "A Blonde in Love."
 E917879 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: Andula | Statement: [A Blonde in Love, mainCharacter, Andula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Andula
Context triple: [A Blonde in Love, mainCharacter, Andula]
  • A. Andul
    Andul is a suburban town in the Howrah district of West Bengal, India, known for its historical temples and proximity to Kolkata.
  • B. Aluta
    Aluta is the historical name of the Olt River, a major waterway flowing through central Romania.
  • C. Errana
    Errana is a medieval Telugu poet known for collaborating on and continuing the composition of the Telugu Mahabharata.
  • D. Comala
    Comala is the haunting, ghostly Mexican town that serves as the central setting of Juan Rulfo’s novel "Pedro Páramo."
  • E. Undu
    Undu is a regional dialect of the Berta language spoken by communities in parts of Ethiopia and Sudan.
  • 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: Andula
Triple: [A Blonde in Love, mainCharacter, Andula]
Generated description
Andula is the naive yet emotionally complex young woman at the heart of Miloš Forman’s Czech New Wave film "A Blonde in Love."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Andula
Target entity description: Andula is the naive yet emotionally complex young woman at the heart of Miloš Forman’s Czech New Wave film "A Blonde in Love."
  • A. Andul
    Andul is a suburban town in the Howrah district of West Bengal, India, known for its historical temples and proximity to Kolkata.
  • B. Aluta
    Aluta is the historical name of the Olt River, a major waterway flowing through central Romania.
  • C. Errana
    Errana is a medieval Telugu poet known for collaborating on and continuing the composition of the Telugu Mahabharata.
  • D. Comala
    Comala is the haunting, ghostly Mexican town that serves as the central setting of Juan Rulfo’s novel "Pedro Páramo."
  • E. Undu
    Undu is a regional dialect of the Berta language spoken by communities in parts of Ethiopia and Sudan.
  • 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_69e50a4af56881908cc395b6687d40a9 completed April 19, 2026, 5 p.m.
NEDg Description generation batch_69e510f9edb4819097e9fa1ce85504ed completed April 19, 2026, 5:29 p.m.
NED2 Entity disambiguation (via description) batch_69e516ac8dec81909c9c1eece372189e completed April 19, 2026, 5:53 p.m.
Created at: April 8, 2026, 9:32 p.m.