Triple

T9614020
Position Surface form Disambiguated ID Type / Status
Subject Bedford North Lawrence High School E232172 entity
Predicate abbreviation P43 FINISHED
Object BNL
BNL is a public high school in Bedford, Indiana, known for its academic programs and competitive athletics, particularly in basketball.
E811067 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: BNL | Statement: [Bedford North Lawrence High School, abbreviation, BNL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BNL
Context triple: [Bedford North Lawrence High School, abbreviation, BNL]
  • A. BNX
    BNX is the IATA airport code for Banja Luka International Airport in Bosnia and Herzegovina.
  • B. BNP
    BNP is the stock ticker symbol for BNP Paribas, a major French international banking and financial services group.
  • C. BNP
    BNP is the National Rail station code assigned to Barnstaple railway station in Devon, England.
  • D. BNS
    BNS is the stock ticker symbol for the Bank of Nova Scotia, one of Canada’s largest multinational banks.
  • E. BNS
    BNS is the main national multipurpose sports stadium in Dhaka, Bangladesh, historically used for major football and cricket events.
  • 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: BNL
Triple: [Bedford North Lawrence High School, abbreviation, BNL]
Generated description
BNL is a public high school in Bedford, Indiana, known for its academic programs and competitive athletics, particularly in basketball.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BNL
Target entity description: BNL is a public high school in Bedford, Indiana, known for its academic programs and competitive athletics, particularly in basketball.
  • A. BNX
    BNX is the IATA airport code for Banja Luka International Airport in Bosnia and Herzegovina.
  • B. BNP
    BNP is the stock ticker symbol for BNP Paribas, a major French international banking and financial services group.
  • C. BNP
    BNP is the National Rail station code assigned to Barnstaple railway station in Devon, England.
  • D. BNS
    BNS is the stock ticker symbol for the Bank of Nova Scotia, one of Canada’s largest multinational banks.
  • E. BNS
    BNS is the main national multipurpose sports stadium in Dhaka, Bangladesh, historically used for major football and cricket events.
  • 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9aaaa47881908d69381d4d11f49b completed April 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69d17958287081908e337bdbe9ea366f completed April 4, 2026, 8:49 p.m.
NEDg Description generation batch_69d17d9d69908190879b160968e41745 completed April 4, 2026, 9:07 p.m.
NED2 Entity disambiguation (via description) batch_69d17e4c9e40819081367d2365bf5dd2 completed April 4, 2026, 9:10 p.m.
Created at: March 30, 2026, 8:09 p.m.