Triple

T6638315
Position Surface form Disambiguated ID Type / Status
Subject Lady Shri Ram College for Women E150514 entity
Predicate shortName P43 FINISHED
Object LSR
LSR is a prestigious women’s college in New Delhi, India, renowned for its academic excellence and affiliation with the University of Delhi.
E607017 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: LSR | Statement: [Lady Shri Ram College for Women, shortName, LSR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LSR
Context triple: [Lady Shri Ram College for Women, shortName, LSR]
  • A. LS
    LS is a base trim level designation commonly used by Chevrolet for entry-level versions of its vehicles, including the Trailblazer.
  • B. LS
    LS is the common abbreviation and nickname for FC Lausanne-Sport, a professional football club based in Lausanne, Switzerland.
  • C. LS
    LS is the IATA airline designator used by the British low-cost carrier Jet2.com.
  • D. LSN
    LSN is the National Rail station code for Livingston North railway station in West Lothian, Scotland.
  • E. LSL
    LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
  • 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: LSR
Triple: [Lady Shri Ram College for Women, shortName, LSR]
Generated description
LSR is a prestigious women’s college in New Delhi, India, renowned for its academic excellence and affiliation with the University of Delhi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LSR
Target entity description: LSR is a prestigious women’s college in New Delhi, India, renowned for its academic excellence and affiliation with the University of Delhi.
  • A. LS
    LS is a base trim level designation commonly used by Chevrolet for entry-level versions of its vehicles, including the Trailblazer.
  • B. LS
    LS is the common abbreviation and nickname for FC Lausanne-Sport, a professional football club based in Lausanne, Switzerland.
  • C. LS
    LS is the IATA airline designator used by the British low-cost carrier Jet2.com.
  • D. LSN
    LSN is the National Rail station code for Livingston North railway station in West Lothian, Scotland.
  • E. LSL
    LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
  • 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff082b0819089f5a69aa67d5346 completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e453cb14819093597dda825b4304 completed March 27, 2026, 8:10 p.m.
NEDg Description generation batch_69c6e5b353c88190817b62290eefc382 completed March 27, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_69c6e669830c8190bc881cb106125ec8 completed March 27, 2026, 8:19 p.m.
Created at: March 27, 2026, 2 p.m.