Triple

T20803487
Position Surface form Disambiguated ID Type / Status
Subject Waste Management, Inc. E512096 entity
Predicate brandName P1500 FINISHED
Object WM
WM is a leading North American waste management and environmental services company providing trash collection, recycling, and disposal solutions for residential, commercial, and industrial customers.
 E1452416 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: WM | Statement: [Waste Management, Inc., brandName, WM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WM
Context triple: [Waste Management, Inc., brandName, WM]
  • A. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • B. WM
    WM is the vehicle registration code for the district of Weilheim-Schongau in Bavaria, Germany.
  • C. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • D. WN
    WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
  • E. WN
    WN is a postcode area in North West England that covers parts of Wigan and surrounding towns.
  • 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: WM
Triple: [Waste Management, Inc., brandName, WM]
Generated description
WM is a leading North American waste management and environmental services company providing trash collection, recycling, and disposal solutions for residential, commercial, and industrial customers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WM
Target entity description: WM is a leading North American waste management and environmental services company providing trash collection, recycling, and disposal solutions for residential, commercial, and industrial customers.
  • A. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • B. WM
    WM is the vehicle registration code for the district of Weilheim-Schongau in Bavaria, Germany.
  • C. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • D. WN
    WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
  • E. WN
    WN is a postcode area in North West England that covers parts of Wigan and surrounding towns.
  • 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_69e0b4cc69f481908e98751e697b9df4 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2b2d5688190aaa58a2594d4787c completed April 21, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09006b92308190be717770884330c2 completed May 16, 2026, 11:40 p.m.
NEDg Description generation batch_6a0901d708688190b4fe5f770c969613 completed May 16, 2026, 11:46 p.m.
NED2 Entity disambiguation (via description) batch_6a09023cf27081908eb246367215ae12 completed May 16, 2026, 11:48 p.m.
Created at: April 16, 2026, 12:39 p.m.