Triple

T15460172
Position Surface form Disambiguated ID Type / Status
Subject National Film School of Denmark E371875 entity
Predicate abbreviation P43 FINISHED
Object DDF
DDF is the commonly used abbreviation for the National Film School of Denmark, a leading institution for film and media education in Denmark.
 E1158771 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: DDF | Statement: [National Film School of Denmark, abbreviation, DDF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DDF
Context triple: [National Film School of Denmark, abbreviation, DDF]
  • A. DDF
    DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
  • B. DFFD
    DFFD is the ICAO airport code for Ouagadougou Airport, the main international airport serving Burkina Faso’s capital city.
  • C. DFF
    DFF is the German abbreviation for Switzerland’s Federal Department of Finance, the national ministry responsible for the country’s financial and budgetary policy.
  • D. DDC
    DDC is the IATA airport code for Dodge City Regional Airport, a public airport serving Dodge City in southwestern Kansas, United States.
  • E. DDC
    DDC is the Dart Dev Compiler, a tool that compiles Dart code to efficient JavaScript for web development.
  • 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: DDF
Triple: [National Film School of Denmark, abbreviation, DDF]
Generated description
DDF is the commonly used abbreviation for the National Film School of Denmark, a leading institution for film and media education in Denmark.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DDF
Target entity description: DDF is the commonly used abbreviation for the National Film School of Denmark, a leading institution for film and media education in Denmark.
  • A. DDF
    DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
  • B. DFFD
    DFFD is the ICAO airport code for Ouagadougou Airport, the main international airport serving Burkina Faso’s capital city.
  • C. DFF
    DFF is the German abbreviation for Switzerland’s Federal Department of Finance, the national ministry responsible for the country’s financial and budgetary policy.
  • D. DDC
    DDC is the Dart Dev Compiler, a tool that compiles Dart code to efficient JavaScript for web development.
  • E. DDC
    DDC is the IATA airport code for Dodge City Regional Airport, a public airport serving Dodge City in southwestern Kansas, United States.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f17663c8190b995c7c3129c90d6 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cfd76cc8190b3d8148ffe872887 completed May 9, 2026, 12:47 p.m.
NEDg Description generation batch_69ff2ead88b0819093046c5f0dae8674 completed May 9, 2026, 12:55 p.m.
NED2 Entity disambiguation (via description) batch_69ff2f4a404c81909a391d3d2cba1ee8 completed May 9, 2026, 12:57 p.m.
Created at: April 10, 2026, 3:32 a.m.