Triple

T3838962
Position Surface form Disambiguated ID Type / Status
Subject Tower of the Americas E93403 entity
Predicate hasRestaurant P4442 FINISHED
Object Chart House
Chart House is a fine-dining seafood and steak restaurant chain in the United States known for its scenic, often waterfront or high-elevation locations.
E393809 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: Chart House | Statement: [Tower of the Americas, hasRestaurant, Chart House]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chart House
Context triple: [Tower of the Americas, hasRestaurant, Chart House]
  • A. Blake House
    Blake House is a historic residence and notable landmark located in the City of Fairfax, Virginia.
  • B. Clock House
    Clock House is a suburban railway station in the London Borough of Bromley that provides local commuter services into central London.
  • C. Ham House
    Ham House is a 17th-century Stuart mansion on the River Thames renowned for its well-preserved period interiors and formal gardens.
  • D. Anderson House
    Anderson House is a historic Beaux-Arts mansion in Washington, D.C., that serves as the headquarters and museum of the Society of the Cincinnati.
  • E. Pat House
    Pat House is a technology executive best known as a co-founder of Siebel Systems, a pioneering customer relationship management (CRM) software company.
  • 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: Chart House
Triple: [Tower of the Americas, hasRestaurant, Chart House]
Generated description
Chart House is a fine-dining seafood and steak restaurant chain in the United States known for its scenic, often waterfront or high-elevation locations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chart House
Target entity description: Chart House is a fine-dining seafood and steak restaurant chain in the United States known for its scenic, often waterfront or high-elevation locations.
  • A. Blake House
    Blake House is a historic residence and notable landmark located in the City of Fairfax, Virginia.
  • B. Clock House
    Clock House is a suburban railway station in the London Borough of Bromley that provides local commuter services into central London.
  • C. Ham House
    Ham House is a 17th-century Stuart mansion on the River Thames renowned for its well-preserved period interiors and formal gardens.
  • D. Anderson House
    Anderson House is a historic Beaux-Arts mansion in Washington, D.C., that serves as the headquarters and museum of the Society of the Cincinnati.
  • E. Pat House
    Pat House is a technology executive best known as a co-founder of Siebel Systems, a pioneering customer relationship management (CRM) software company.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeb9f305c8190b71ac53bbb0c4beb completed March 9, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5040835dc81909ecf5053128f1cc7 completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b507cfee048190a41ad30f4ceaf6c8 completed March 14, 2026, 7:01 a.m.
NED2 Entity disambiguation (via description) batch_69b50857e9ec8190bb03f13c4573b779 completed March 14, 2026, 7:03 a.m.
Created at: March 9, 2026, 3:18 p.m.