Triple

T5428373
Position Surface form Disambiguated ID Type / Status
Subject Olympia Entertainment E121420 entity
Predicate associatedWithBrand P2830 FINISHED
Object Hockeytown
Hockeytown is a popular marketing nickname and brand associated with Detroit’s passionate hockey culture and the NHL’s Detroit Red Wings.
 E518604 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: Hockeytown | Statement: [Olympia Entertainment, associatedWithBrand, Hockeytown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hockeytown
Context triple: [Olympia Entertainment, associatedWithBrand, Hockeytown]
  • A. Hat City
    Hat City is the nickname of Danbury, Connecticut, reflecting its historic prominence as a major center of hat manufacturing in the United States.
  • B. Jones Falls
    Jones Falls is a significant stream in central Maryland that flows through Baltimore before joining the Patapsco River.
  • C. Beantown
    Beantown is a popular nickname for the city of Boston, Massachusetts, often used in informal and cultural references to the city.
  • D. Houton
    Houton is a small settlement and ferry port in Orkney, Scotland, serving as a key departure point for ferries to nearby islands such as Hoy and Flotta.
  • E. Bear Town
    Bear Town is the traditional nickname of Congleton, a historic market town in Cheshire, England.
  • 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: Hockeytown
Triple: [Olympia Entertainment, associatedWithBrand, Hockeytown]
Generated description
Hockeytown is a popular marketing nickname and brand associated with Detroit’s passionate hockey culture and the NHL’s Detroit Red Wings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hockeytown
Target entity description: Hockeytown is a popular marketing nickname and brand associated with Detroit’s passionate hockey culture and the NHL’s Detroit Red Wings.
  • A. Hat City
    Hat City is the nickname of Danbury, Connecticut, reflecting its historic prominence as a major center of hat manufacturing in the United States.
  • B. Jones Falls
    Jones Falls is a significant stream in central Maryland that flows through Baltimore before joining the Patapsco River.
  • C. Beantown
    Beantown is a popular nickname for the city of Boston, Massachusetts, often used in informal and cultural references to the city.
  • D. Houton
    Houton is a small settlement and ferry port in Orkney, Scotland, serving as a key departure point for ferries to nearby islands such as Hoy and Flotta.
  • E. Bear Town
    Bear Town is the traditional nickname of Congleton, a historic market town in Cheshire, England.
  • 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd881998308190a071af0fe44997bc completed March 20, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ac2e1e88190a624ba277eca3d03 completed March 22, 2026, 12:41 a.m.
NEDg Description generation batch_69bf3b592a08819090e2873bcf4e797f completed March 22, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_69bf3c0b9e5481909101eccbd55f24b2 completed March 22, 2026, 12:47 a.m.
Created at: March 20, 2026, 2:06 p.m.