Triple

T6428738
Position Surface form Disambiguated ID Type / Status
Subject Federal Ministry of Justice of Germany E128124 entity
Predicate formerShortName P65 FINISHED
Object BMJV
BMJV was the former abbreviation for Germany’s Federal Ministry of Justice, used before its name change and rebranding.
E592465 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: BMJV | Statement: [Federal Ministry of Justice of Germany, formerShortName, BMJV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BMJV
Context triple: [Federal Ministry of Justice of Germany, formerShortName, BMJV]
  • A. BMUV
    BMUV is the German federal ministry responsible for environmental protection, nature conservation, nuclear safety, and consumer protection policy.
  • B. BMVI
    BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
  • C. BMVg
    BMVg is the commonly used abbreviation for Germany’s Federal Ministry of Defence, the government department responsible for the country’s military and defense policy.
  • D. MBJ
    MBJ is the IATA airport code for Sangster International Airport, the main tourist gateway serving Montego Bay, Jamaica.
  • E. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • 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: BMJV
Triple: [Federal Ministry of Justice of Germany, formerShortName, BMJV]
Generated description
BMJV was the former abbreviation for Germany’s Federal Ministry of Justice, used before its name change and rebranding.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BMJV
Target entity description: BMJV was the former abbreviation for Germany’s Federal Ministry of Justice, used before its name change and rebranding.
  • A. BMUV
    BMUV is the German federal ministry responsible for environmental protection, nature conservation, nuclear safety, and consumer protection policy.
  • B. BMVI
    BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
  • C. BMVg
    BMVg is the commonly used abbreviation for Germany’s Federal Ministry of Defence, the government department responsible for the country’s military and defense policy.
  • D. MBJ
    MBJ is the IATA airport code for Sangster International Airport, the main tourist gateway serving Montego Bay, Jamaica.
  • E. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06922a27881908c5571f2aa31e0c1 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640e678608190b5a1dcd1076bc1f2 completed March 27, 2026, 8:33 a.m.
NEDg Description generation batch_69c641d6024c8190996aae40851a3b73 completed March 27, 2026, 8:37 a.m.
NED2 Entity disambiguation (via description) batch_69c6425e0a348190bc1eb90eb8c00597 completed March 27, 2026, 8:39 a.m.
Created at: March 22, 2026, 4:44 p.m.