Triple

T8285421
Position Surface form Disambiguated ID Type / Status
Subject Linux Security Modules API E193776 entity
Predicate alsoKnownAs P39 FINISHED
Object LSM API
LSM API is the kernel-level interface in Linux that allows security modules to enforce access control and other security policies.
 E724148 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 API | Statement: [Linux Security Modules API, alsoKnownAs, LSM API]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LSM API
Context triple: [Linux Security Modules API, alsoKnownAs, LSM API]
  • A. 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.
  • B. LSL
    LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
  • C. LSI
    LSI is the three-letter IATA airport code for Sumburgh Airport in the Shetland Islands, Scotland.
  • D. Log-Structured Merge-Tree
    A Log-Structured Merge-Tree (LSM-tree) is a write-optimized data structure that organizes data in sequential logs and periodically merges them to provide efficient writes and good read performance for key-value storage systems.
  • E. LS&MS
    LS&MS is the abbreviation for the Lake Shore and Michigan Southern Railway, a historic U.S. railroad that operated routes primarily around the Great Lakes region.
  • 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 API
Triple: [Linux Security Modules API, alsoKnownAs, LSM API]
Generated description
LSM API is the kernel-level interface in Linux that allows security modules to enforce access control and other security policies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LSM API
Target entity description: LSM API is the kernel-level interface in Linux that allows security modules to enforce access control and other security policies.
  • A. 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.
  • B. LSL
    LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
  • C. LSI
    LSI is the three-letter IATA airport code for Sumburgh Airport in the Shetland Islands, Scotland.
  • D. Log-Structured Merge-Tree
    A Log-Structured Merge-Tree (LSM-tree) is a write-optimized data structure that organizes data in sequential logs and periodically merges them to provide efficient writes and good read performance for key-value storage systems.
  • E. LS&MS
    LS&MS is the abbreviation for the Lake Shore and Michigan Southern Railway, a historic U.S. railroad that operated routes primarily around the Great Lakes region.
  • 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_69ca82e32db481908b72f3804fa71152 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7ad20ae481908179aba245c73fad completed March 31, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd687e64a08190a45a1cf5f5c32291 completed April 1, 2026, 6:48 p.m.
NEDg Description generation batch_69cd6d55196881909cf5ec925792e09f completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7e2bdae08190adc51e904e85695e completed April 1, 2026, 8:21 p.m.
Created at: March 30, 2026, 5:52 p.m.