Triple

T5747568
Position Surface form Disambiguated ID Type / Status
Subject West Edmonton Mall E126769 entity
Predicate hasNickName P39 FINISHED
Object WEM
WEM is a massive shopping and entertainment complex in Edmonton, Alberta, known as one of the largest malls in North America.
 E544236 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: WEM | Statement: [West Edmonton Mall, hasNickName, WEM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WEM
Context triple: [West Edmonton Mall, hasNickName, WEM]
  • A. Wem
    Wem is a small market town and civil parish in the county of Shropshire, England.
  • B. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • C. WAMO
    WAMO is a Pittsburgh-area radio station historically known for its urban contemporary and hip-hop programming serving the region’s Black community.
  • D. WMC
    WMC is the commonly used abbreviation for the World Methodist Council, a worldwide association of Methodist churches and related denominations.
  • E. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • 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: WEM
Triple: [West Edmonton Mall, hasNickName, WEM]
Generated description
WEM is a massive shopping and entertainment complex in Edmonton, Alberta, known as one of the largest malls in North America.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WEM
Target entity description: WEM is a massive shopping and entertainment complex in Edmonton, Alberta, known as one of the largest malls in North America.
  • A. Wem
    Wem is a small market town and civil parish in the county of Shropshire, England.
  • B. WM
    WM was the reporting mark for the Western Maryland Railway, a regional U.S. railroad that later became part of the Chessie System.
  • C. WAMO
    WAMO is a Pittsburgh-area radio station historically known for its urban contemporary and hip-hop programming serving the region’s Black community.
  • D. WMC
    WMC is the commonly used abbreviation for the World Methodist Council, a worldwide association of Methodist churches and related denominations.
  • E. WUN
    WUN is a global consortium of research-intensive universities that collaborate on international education and research initiatives.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02885b0288190835809681a364b1f completed March 22, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e30fe98819096ad6e09fbd463b5 completed March 22, 2026, 11:41 p.m.
NEDg Description generation batch_69c08d5a3fbc8190bd0a0862ad6ae66d completed March 23, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69c08dc4d12c8190a7a245d583ef08d4 completed March 23, 2026, 12:48 a.m.
Created at: March 22, 2026, 3:48 p.m.