Triple

T414342
Position Surface form Disambiguated ID Type / Status
Subject Wage and Hour Division E9558 entity
Predicate abbreviation P43 FINISHED
Object WHD
WHD is the U.S. Department of Labor’s Wage and Hour Division, the federal agency responsible for enforcing minimum wage, overtime pay, child labor, and other key labor standards.
 E52519 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: WHD | Statement: [Wage and Hour Division, abbreviation, WHD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WHD
Context triple: [Wage and Hour Division, abbreviation, WHD]
  • A. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • B. WHR
    WHR is the commonly used abbreviation for the World Health Report, the World Health Organization’s flagship publication on global health statistics, trends, and policy.
  • C. Ware
    Ware was the plaintiff in the landmark U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • E. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • 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: WHD
Triple: [Wage and Hour Division, abbreviation, WHD]
Generated description
WHD is the U.S. Department of Labor’s Wage and Hour Division, the federal agency responsible for enforcing minimum wage, overtime pay, child labor, and other key labor standards.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WHD
Target entity description: WHD is the U.S. Department of Labor’s Wage and Hour Division, the federal agency responsible for enforcing minimum wage, overtime pay, child labor, and other key labor standards.
  • A. WD
    WD is a consumer-facing brand of Western Digital known for its hard drives, solid-state drives, and other data storage products.
  • B. WHR
    WHR is the commonly used abbreviation for the World Health Report, the World Health Organization’s flagship publication on global health statistics, trends, and policy.
  • C. Ware
    Ware was the plaintiff in the landmark U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • E. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ee2d6fe481908ff70ab7d043bb3e completed Feb. 28, 2026, 1:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b4ce1648190b1f46ba33d7cf946 completed March 1, 2026, 10:56 a.m.
NEDg Description generation batch_69a41bc18b388190ae97d97656294e7b completed March 1, 2026, 10:58 a.m.
NED2 Entity disambiguation (via description) batch_69a422983e708190904cd891d3996338 completed March 1, 2026, 11:27 a.m.
Created at: Feb. 28, 2026, 1:09 p.m.