Triple

T19598342
Position Surface form Disambiguated ID Type / Status
Subject Federal Institute for Risk Assessment E470404 entity
Predicate abbreviation P43 FINISHED
Object BfR
BfR is Germany’s Federal Institute for Risk Assessment, a scientific body that evaluates health risks related to food, chemicals, and consumer products.
 E1384916 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: BfR | Statement: [Federal Institute for Risk Assessment, abbreviation, BfR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BfR
Context triple: [Federal Institute for Risk Assessment, abbreviation, BfR]
  • A. BMBF
    BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
  • B. BfS
    BfS is Germany’s Federal Office for Radiation Protection, the national authority responsible for monitoring and regulating radiation exposure and nuclear safety.
  • C. BfV
    BfV is Germany’s domestic intelligence agency responsible for protecting the constitutional order and countering threats such as extremism and espionage.
  • D. BMEL
    BMEL is the abbreviation for Germany’s Federal Ministry responsible for national policies on food, agriculture, and consumer protection in these areas.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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: BfR
Triple: [Federal Institute for Risk Assessment, abbreviation, BfR]
Generated description
BfR is Germany’s Federal Institute for Risk Assessment, a scientific body that evaluates health risks related to food, chemicals, and consumer products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BfR
Target entity description: BfR is Germany’s Federal Institute for Risk Assessment, a scientific body that evaluates health risks related to food, chemicals, and consumer products.
  • A. BMBF
    BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
  • B. BfS
    BfS is Germany’s Federal Office for Radiation Protection, the national authority responsible for monitoring and regulating radiation exposure and nuclear safety.
  • C. BfV
    BfV is Germany’s domestic intelligence agency responsible for protecting the constitutional order and countering threats such as extremism and espionage.
  • D. BMEL
    BMEL is the abbreviation for Germany’s Federal Ministry responsible for national policies on food, agriculture, and consumer protection in these areas.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407c52c081908704d3a4dd6e853b completed April 20, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a075f1be2d48190a1beec726ea4e410 completed May 15, 2026, 5:59 p.m.
NEDg Description generation batch_6a075fde0d8c8190aefc4a06beda2c79 completed May 15, 2026, 6:03 p.m.
NED2 Entity disambiguation (via description) batch_6a076039f7188190add1c65a4a9e32ce completed May 15, 2026, 6:04 p.m.
Created at: April 10, 2026, 1:43 p.m.