Triple

T6293642
Position Surface form Disambiguated ID Type / Status
Subject law of large numbers E141078 entity
Predicate alsoKnownAs P39 FINISHED
Object LLN
LLN is a fundamental theorem in probability theory stating that as the number of independent, identically distributed trials increases, the sample average converges to the expected value.
 E582381 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: LLN | Statement: [law of large numbers, alsoKnownAs, LLN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LLN
Context triple: [law of large numbers, alsoKnownAs, LLN]
  • A. NNL
    NNL is the commonly used abbreviation for the Negro National League, a pioneering professional baseball league that was a cornerstone of Negro league baseball in the early 20th century.
  • B. LL
    LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
  • C. NLL
    The NLL (National Lacrosse League) is North America’s premier professional indoor box lacrosse league.
  • D. LN
    LN is the postcode area designation for Lincoln and its surrounding region in the United Kingdom.
  • E. LN1
    LN1 is the first French high-speed rail line (LGV Sud-Est), connecting Paris to Lyon and pioneering the TGV network.
  • 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: LLN
Triple: [law of large numbers, alsoKnownAs, LLN]
Generated description
LLN is a fundamental theorem in probability theory stating that as the number of independent, identically distributed trials increases, the sample average converges to the expected value.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LLN
Target entity description: LLN is a fundamental theorem in probability theory stating that as the number of independent, identically distributed trials increases, the sample average converges to the expected value.
  • A. NNL
    NNL is the commonly used abbreviation for the Negro National League, a pioneering professional baseball league that was a cornerstone of Negro league baseball in the early 20th century.
  • B. LL
    LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
  • C. NLL
    The NLL (National Lacrosse League) is North America’s premier professional indoor box lacrosse league.
  • D. LN
    LN is the postcode area designation for Lincoln and its surrounding region in the United Kingdom.
  • E. LN1
    LN1 is the first French high-speed rail line (LGV Sud-Est), connecting Paris to Lyon and pioneering the TGV network.
  • 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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06438654481908c9833c5f0d61773 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c51988f1388190b36212b0d9756863 completed March 26, 2026, 11:33 a.m.
NEDg Description generation batch_69c51e7ce1b4819090b5bef16a9ea95e completed March 26, 2026, 11:54 a.m.
NED2 Entity disambiguation (via description) batch_69c59285696c819099c31868f6b758dc completed March 26, 2026, 8:09 p.m.
Created at: March 22, 2026, 4:27 p.m.