Triple

T16426845
Position Surface form Disambiguated ID Type / Status
Subject Ministry of the Interior of the GDR E398964 entity
Predicate shortName P43 FINISHED
Object MdI
MdI was the common abbreviation for the Ministry of the Interior of the German Democratic Republic, the state body responsible for internal security, police, and administrative affairs.
E1212797 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: MdI | Statement: [Ministry of the Interior of the GDR, shortName, MdI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MdI
Context triple: [Ministry of the Interior of the GDR, shortName, MdI]
  • A. MD
    MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
  • B. MD
    MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
  • C. MD
    MD is the station code used to identify Maitland railway station in New South Wales, Australia.
  • D. MD
    MD is the official two-letter United States Postal Service abbreviation used to designate the state of Maryland.
  • E. Ramatlabama
    Ramatlabama is a village and key border post between Botswana and South Africa that serves as an important road and rail crossing point.
  • 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: MdI
Triple: [Ministry of the Interior of the GDR, shortName, MdI]
Generated description
MdI was the common abbreviation for the Ministry of the Interior of the German Democratic Republic, the state body responsible for internal security, police, and administrative affairs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MdI
Target entity description: MdI was the common abbreviation for the Ministry of the Interior of the German Democratic Republic, the state body responsible for internal security, police, and administrative affairs.
  • A. MD
    MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
  • B. MD
    MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
  • C. MD
    MD is the station code used to identify Maitland railway station in New South Wales, Australia.
  • D. MD
    MD is the official two-letter United States Postal Service abbreviation used to designate the state of Maryland.
  • E. Ramatlabama
    Ramatlabama is a village and key border post between Botswana and South Africa that serves as an important road and rail crossing point.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328fb6cd881908fb6cd1c60f5ac3c completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458168888190bd0be495efa5c563 completed May 10, 2026, 8:44 a.m.
NEDg Description generation batch_6a004621f0908190ad97a15fec619765 completed May 10, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_6a0046a88e048190baa78506808171b8 completed May 10, 2026, 8:49 a.m.
Created at: April 10, 2026, 5:09 a.m.