Triple

T1602341
Position Surface form Disambiguated ID Type / Status
Subject AO Arena E34421 entity
Predicate sponsor P67 FINISHED
Object AO
AO is a UK-based online electricals retailer known for selling appliances and consumer electronics through its e-commerce platform and associated services.
 E181335 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: AO | Statement: [AO Arena, sponsor, AO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AO
Context triple: [AO Arena, sponsor, AO]
  • A. AO
    AO is the two-letter ISO 3166-1 alpha-2 country code representing Angola in international standards and systems.
  • B. AO
    AO is the commonly used abbreviation for the Administrative Office of the United States Courts, the federal agency that provides administrative support to the U.S. federal judiciary.
  • C. AO
    AO is the vehicle registration code used on license plates for vehicles registered in Italy’s Aosta Valley region.
  • D. AO
    AO is the common abbreviation for Agent Orange, a highly toxic herbicide and defoliant used by the U.S. military during the Vietnam War that caused widespread environmental damage and severe health effects.
  • E. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • 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: AO
Triple: [AO Arena, sponsor, AO]
Generated description
AO is a UK-based online electricals retailer known for selling appliances and consumer electronics through its e-commerce platform and associated services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AO
Target entity description: AO is a UK-based online electricals retailer known for selling appliances and consumer electronics through its e-commerce platform and associated services.
  • A. AO
    AO is the two-letter ISO 3166-1 alpha-2 country code representing Angola in international standards and systems.
  • B. AO
    AO is the commonly used abbreviation for the Administrative Office of the United States Courts, the federal agency that provides administrative support to the U.S. federal judiciary.
  • C. AO
    AO is the vehicle registration code used on license plates for vehicles registered in Italy’s Aosta Valley region.
  • D. AO
    AO is the common abbreviation for Agent Orange, a highly toxic herbicide and defoliant used by the U.S. military during the Vietnam War that caused widespread environmental damage and severe health effects.
  • E. ANA
    ANA is the standard three-letter abbreviation used for the Anaheim Ducks, a professional ice hockey team in the National Hockey League.
  • 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62292d1c819080b597199dc6b8d5 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46ad15b081908b59df18224c7a8f completed March 8, 2026, 9:51 a.m.
NEDg Description generation batch_69ad4740c2788190a7ce80cb978a0b19 completed March 8, 2026, 9:54 a.m.
NED2 Entity disambiguation (via description) batch_69ad47bb63248190ba240c004b434686 completed March 8, 2026, 9:56 a.m.
Created at: March 4, 2026, 7:28 p.m.