Triple

T3400942
Position Surface form Disambiguated ID Type / Status
Subject Babelsberg Film Studio E71648 entity
Predicate usedBy P260 FINISHED
Object UFA
UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
 E355973 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: UFA | Statement: [Babelsberg Film Studio, usedBy, UFA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UFA
Context triple: [Babelsberg Film Studio, usedBy, UFA]
  • A. UWF
    UWF is a public university in Pensacola, Florida, offering undergraduate and graduate programs across a range of disciplines.
  • B. GUF
    GUF is the three-letter ISO 3166-1 alpha-3 country code assigned to French Guiana.
  • C. UZ
    UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
  • D. UA
    UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
  • E. UA
    UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
  • 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: UFA
Triple: [Babelsberg Film Studio, usedBy, UFA]
Generated description
UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UFA
Target entity description: UFA (Universum Film AG) was a major German film production and distribution company, especially prominent during the Weimar Republic and early 20th-century cinema.
  • A. UWF
    UWF is a public university in Pensacola, Florida, offering undergraduate and graduate programs across a range of disciplines.
  • B. GUF
    GUF is the three-letter ISO 3166-1 alpha-3 country code assigned to French Guiana.
  • C. UZ
    UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
  • D. UA
    UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
  • E. UA
    UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
  • 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_69ad85aac4808190a092c9cc8911f584 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb8c80e0081909c3d5f95ab6f55a0 completed March 8, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bd2f8a481908554635ed59c8939 completed March 12, 2026, 11:27 p.m.
NEDg Description generation batch_69b34e4792608190b74e02e065d4bc68 completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b3525f44948190af72b177193edca4 completed March 12, 2026, 11:55 p.m.
Created at: March 8, 2026, 3:14 p.m.