Triple

T21088133
Position Surface form Disambiguated ID Type / Status
Subject Jerome Sacks E519556 entity
Predicate hasPublishedIn P309 FINISHED
Object Technometrics NE NERFINISHED

How this triple was built (2 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: Technometrics | Statement: [Jerome Sacks, hasPublishedIn, Technometrics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Technometrics
Context triple: [Jerome Sacks, hasPublishedIn, Technometrics]
  • A. Technometrics chosen
    Technometrics is a peer-reviewed journal focusing on the development and application of statistical methods in the physical, chemical, and engineering sciences.
  • B. The American Statistician
    The American Statistician is a peer-reviewed journal that features articles on statistical practice, theory, and education, published by the American Statistical Association.
  • C. Metrologia
    Metrologia is a leading international scientific journal focused on the science of measurement, including fundamental metrology, standards, and precision measurement techniques.
  • D. Journal of the American Statistical Association
    The Journal of the American Statistical Association is a leading peer-reviewed scholarly journal covering theoretical and applied statistics across a wide range of scientific disciplines.
  • E. International Recommendations for Industrial Statistics
    International Recommendations for Industrial Statistics is a key United Nations Statistics Division framework that provides internationally agreed concepts, definitions, and methodological guidelines for the collection and compilation of industrial statistics.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094cebe08190bb10f51a45c244ec completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:50 p.m.