Triple

T11320956
Position Surface form Disambiguated ID Type / Status
Subject S&P BSE SENSEX E268091 entity
Predicate dataVendorCode P508 FINISHED
Object ^BSESN
^BSESN is the ticker symbol for the S&P BSE SENSEX, the benchmark stock market index of the Bombay Stock Exchange in India.
 E919031 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: ^BSESN | Statement: [S&P BSE SENSEX, dataVendorCode, ^BSESN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ^BSESN
Context triple: [S&P BSE SENSEX, dataVendorCode, ^BSESN]
  • A. BES
    BES is the international vehicle registration code used for the Caribbean Netherlands islands of Bonaire, Sint Eustatius, and Saba.
  • B. BESE
    BESE is the acronym for the Massachusetts Board of Elementary and Secondary Education, the state body responsible for overseeing public K–12 education policy and standards in Massachusetts.
  • C. BSEC
    BSEC is a regional intergovernmental organization that promotes economic cooperation and development among countries in the Black Sea region.
  • 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: ^BSESN
Triple: [S&P BSE SENSEX, dataVendorCode, ^BSESN]
Generated description
^BSESN is the ticker symbol for the S&P BSE SENSEX, the benchmark stock market index of the Bombay Stock Exchange in India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ^BSESN
Target entity description: ^BSESN is the ticker symbol for the S&P BSE SENSEX, the benchmark stock market index of the Bombay Stock Exchange in India.
  • A. BES
    BES is the international vehicle registration code used for the Caribbean Netherlands islands of Bonaire, Sint Eustatius, and Saba.
  • B. BESE
    BESE is the acronym for the Massachusetts Board of Elementary and Secondary Education, the state body responsible for overseeing public K–12 education policy and standards in Massachusetts.
  • C. BSEC
    BSEC is a regional intergovernmental organization that promotes economic cooperation and development among countries in the Black Sea region.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9dff37081909622623e66e17ccd completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525e2549081909ec99e4c7006fd66 completed April 19, 2026, 6:58 p.m.
NEDg Description generation batch_69e52c82b6108190aec9b6e9d726f803 completed April 19, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_69e531b079708190ac9e19127d36a848 completed April 19, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:32 p.m.