Triple

T11874184
Position Surface form Disambiguated ID Type / Status
Subject German Social Accident Insurance E282480 entity
Predicate abbreviation P43 FINISHED
Object DGUV
DGUV is the German Social Accident Insurance institution responsible for statutory accident insurance and prevention for workers and students in Germany.
 E950647 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: DGUV | Statement: [German Social Accident Insurance, abbreviation, DGUV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DGUV
Context triple: [German Social Accident Insurance, abbreviation, DGUV]
  • A. DGS
    DGS is the California state agency that provides centralized business, procurement, real estate, and support services to other government departments.
  • B. DGS
    The DGS was the notorious political police force of Portugal’s Estado Novo dictatorship, responsible for repressing dissent and persecuting regime opponents.
  • C. ГД
    ГД is the station code used to designate the Gostiyny Dvor metro station in Saint Petersburg, Russia.
  • D. DG
    DG is the abbreviation for the German-speaking Community, the small German-language region and federal community in eastern Belgium.
  • E. DG
    DG is the stock ticker symbol for Data General, a former American minicomputer manufacturer prominent in the 1970s and 1980s.
  • 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: DGUV
Triple: [German Social Accident Insurance, abbreviation, DGUV]
Generated description
DGUV is the German Social Accident Insurance institution responsible for statutory accident insurance and prevention for workers and students in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DGUV
Target entity description: DGUV is the German Social Accident Insurance institution responsible for statutory accident insurance and prevention for workers and students in Germany.
  • A. DGS
    The DGS was the notorious political police force of Portugal’s Estado Novo dictatorship, responsible for repressing dissent and persecuting regime opponents.
  • B. DGS
    DGS is the California state agency that provides centralized business, procurement, real estate, and support services to other government departments.
  • C. ГД
    ГД is the station code used to designate the Gostiyny Dvor metro station in Saint Petersburg, Russia.
  • D. DG
    DG is the abbreviation for the German-speaking Community, the small German-language region and federal community in eastern Belgium.
  • E. DG
    DG is the stock ticker symbol for Data General, a former American minicomputer manufacturer prominent in the 1970s and 1980s.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1a22448190bd0722188c14d7bd completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281cac9a48190b4b0f4c53b41110f completed April 29, 2026, 10:10 p.m.
NEDg Description generation batch_69f28a9378348190866e38259cc9467e completed April 29, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_69f28c5f7638819098aa93aa1610ca0a completed April 29, 2026, 10:55 p.m.
Created at: April 8, 2026, 9:43 p.m.