Triple

T6251206
Position Surface form Disambiguated ID Type / Status
Subject Vagelos Life Sciences and Management Program E140049 entity
Predicate shortName P43 FINISHED
Object LSM
LSM is an undergraduate dual-degree program at the University of Pennsylvania that integrates rigorous training in life sciences with business and management education.
 E579615 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: LSM | Statement: [Vagelos Life Sciences and Management Program, shortName, LSM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LSM
Context triple: [Vagelos Life Sciences and Management Program, shortName, LSM]
  • A. LSMD
    LSMD is the ICAO airport code assigned to Dübendorf Air Base in Switzerland.
  • B. B-tree
    A B-tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, commonly used to implement database indexes.
  • C. LSN
    LSN is the National Rail station code for Livingston North railway station in West Lothian, Scotland.
  • D. HSM
    A Hardware Security Module (HSM) is a dedicated, tamper-resistant device used to securely generate, store, and manage cryptographic keys and perform sensitive cryptographic operations.
  • E. LSI
    LSI is the three-letter IATA airport code for Sumburgh Airport in the Shetland Islands, Scotland.
  • 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: LSM
Triple: [Vagelos Life Sciences and Management Program, shortName, LSM]
Generated description
LSM is an undergraduate dual-degree program at the University of Pennsylvania that integrates rigorous training in life sciences with business and management education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LSM
Target entity description: LSM is an undergraduate dual-degree program at the University of Pennsylvania that integrates rigorous training in life sciences with business and management education.
  • A. LSMD
    LSMD is the ICAO airport code assigned to Dübendorf Air Base in Switzerland.
  • B. B-tree
    A B-tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, commonly used to implement database indexes.
  • C. LSN
    LSN is the National Rail station code for Livingston North railway station in West Lothian, Scotland.
  • D. HSM
    A Hardware Security Module (HSM) is a dedicated, tamper-resistant device used to securely generate, store, and manage cryptographic keys and perform sensitive cryptographic operations.
  • E. LSI
    LSI is the three-letter IATA airport code for Sumburgh Airport in the Shetland Islands, Scotland.
  • 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_69c008b4858c819095b0199114a9a87b completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0633fb2ac8190b71b8e35fa923300 completed March 22, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c244240b448190be3645177194ced6 completed March 24, 2026, 7:58 a.m.
NEDg Description generation batch_69c2756cf5c88190aed2c5e0916082e7 completed March 24, 2026, 11:28 a.m.
NED2 Entity disambiguation (via description) batch_69c275d913cc8190be3770f12c271226 completed March 24, 2026, 11:30 a.m.
Created at: March 22, 2026, 4:24 p.m.