Triple

T1471461
Position Surface form Disambiguated ID Type / Status
Subject Federal Ministry of Education and Research E27143 entity
Predicate shortName P43 FINISHED
Object BMBF
BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
 E168692 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: BMBF | Statement: [Federal Ministry of Education and Research, shortName, BMBF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BMBF
Context triple: [Federal Ministry of Education and Research, shortName, BMBF]
  • A. BMEL
    BMEL is the abbreviation for Germany’s Federal Ministry responsible for national policies on food, agriculture, and consumer protection in these areas.
  • B. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • C. MFS
    MFS (Macintosh File System) is the original flat file system used by early Macintosh computers before the introduction of the hierarchical HFS.
  • D. MURI
    MURI is a U.S. Department of Defense research program that funds large, multidisciplinary university teams to address complex, high-impact scientific and engineering challenges.
  • E. BdM
    BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
  • 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: BMBF
Triple: [Federal Ministry of Education and Research, shortName, BMBF]
Generated description
BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BMBF
Target entity description: BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
  • A. BMEL
    BMEL is the abbreviation for Germany’s Federal Ministry responsible for national policies on food, agriculture, and consumer protection in these areas.
  • B. MAB
    MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
  • C. MFS
    MFS (Macintosh File System) is the original flat file system used by early Macintosh computers before the introduction of the hierarchical HFS.
  • D. MURI
    MURI is a U.S. Department of Defense research program that funds large, multidisciplinary university teams to address complex, high-impact scientific and engineering challenges.
  • E. BdM
    BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
  • 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_69a496d25d6881909dbd84f86d763992 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c5db55948190ae5262a70a161b87 completed March 1, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15a74fbc8190b53511713032dc63 completed March 8, 2026, 6:22 a.m.
NEDg Description generation batch_69ad162d7d08819085108fa5bb33f40f completed March 8, 2026, 6:24 a.m.
NED2 Entity disambiguation (via description) batch_69ad16a5c76c8190a0bb3ccf5557b1b0 completed March 8, 2026, 6:26 a.m.
Created at: March 1, 2026, 8:01 p.m.