Triple

T740285
Position Surface form Disambiguated ID Type / Status
Subject Decent Work Agenda E15228 entity
Predicate abbreviation P43 FINISHED
Object DWA
DWA is the commonly used abbreviation for the International Labour Organization’s Decent Work Agenda, a global framework promoting fair, secure, and dignified employment.
 E87380 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: DWA | Statement: [Decent Work Agenda, abbreviation, DWA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DWA
Context triple: [Decent Work Agenda, abbreviation, DWA]
  • A. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • B. WDG
    WDG is the abbreviated name for Wizards District Gaming, the NBA 2K League esports team affiliated with the Washington Wizards.
  • C. KADW
    KADW is the ICAO airport code for Joint Base Andrews, a major U.S. military airfield near Washington, D.C.
  • D. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • E. DAK
    DAK is the abbreviation for the German Afrika Korps, the German expeditionary force that fought in North Africa during World War II under commanders such as Erwin Rommel.
  • 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: DWA
Triple: [Decent Work Agenda, abbreviation, DWA]
Generated description
DWA is the commonly used abbreviation for the International Labour Organization’s Decent Work Agenda, a global framework promoting fair, secure, and dignified employment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DWA
Target entity description: DWA is the commonly used abbreviation for the International Labour Organization’s Decent Work Agenda, a global framework promoting fair, secure, and dignified employment.
  • A. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • B. WDG
    WDG is the abbreviated name for Wizards District Gaming, the NBA 2K League esports team affiliated with the Washington Wizards.
  • C. KADW
    KADW is the ICAO airport code for Joint Base Andrews, a major U.S. military airfield near Washington, D.C.
  • D. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • E. DAK
    DAK is the abbreviation for the German Afrika Korps, the German expeditionary force that fought in North Africa during World War II under commanders such as Erwin Rommel.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f4ccb48190a4eb8679a59d8e24 completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a63f9288190b86e4a75467acce0 completed March 3, 2026, 2:41 a.m.
NEDg Description generation batch_69a64aef14c48190b947a4c3a7becc0f completed March 3, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_69a64b80d5fc81909e69832457569064 completed March 3, 2026, 2:46 a.m.
Created at: March 1, 2026, 7:37 p.m.