Triple

T21993521
Position Surface form Disambiguated ID Type / Status
Subject Black Book E543146 entity
Predicate producer P490 FINISHED
Object San Fu Maltha
San Fu Maltha is a Dutch film producer known for his work on notable European films, including the World War II drama "Black Book."
 E1512532 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: San Fu Maltha | Statement: [Black Book, producer, San Fu Maltha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Fu Maltha
Context triple: [Black Book, producer, San Fu Maltha]
  • A. Saffais
    Saffais is a small commune in the Meurthe-et-Moselle department of northeastern France.
  • B. Molazzana
    Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
  • C. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • D. Malauzat
    Malauzat is a small commune in the Puy-de-Dôme department of central France, situated within the Auvergne region.
  • E. Malba
    Malba is an affluent residential neighborhood in the northeastern part of Queens, New York City, known for its large waterfront homes and quiet, suburban character.
  • 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: San Fu Maltha
Triple: [Black Book, producer, San Fu Maltha]
Generated description
San Fu Maltha is a Dutch film producer known for his work on notable European films, including the World War II drama "Black Book."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: San Fu Maltha
Target entity description: San Fu Maltha is a Dutch film producer known for his work on notable European films, including the World War II drama "Black Book."
  • A. Saffais
    Saffais is a small commune in the Meurthe-et-Moselle department of northeastern France.
  • B. Molazzana
    Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
  • C. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • D. Malauzat
    Malauzat is a small commune in the Puy-de-Dôme department of central France, situated within the Auvergne region.
  • E. Malba
    Malba is an affluent residential neighborhood in the northeastern part of Queens, New York City, known for its large waterfront homes and quiet, suburban character.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1270f77fc8190aadcc02760d65ac0 completed April 28, 2026, 9:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a6d85f104819088dba8d0bf347fbe completed May 18, 2026, 1:38 a.m.
NEDg Description generation batch_6a0a6e556f3c8190927d1c0cba23463c completed May 18, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_6a0a6f3de2e88190824c9cc266c7ee8c completed May 18, 2026, 1:45 a.m.
Created at: April 16, 2026, 8:17 p.m.