Triple

T7802583
Position Surface form Disambiguated ID Type / Status
Subject Department of Mathematical Sciences, Carnegie Mellon University E180464 entity
Predicate collaboratesWith P37 FINISHED
Object Department of Statistics and Data Science, Carnegie Mellon University E672682 NE FINISHED

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: Department of Statistics and Data Science, Carnegie Mellon University | Statement: [Department of Mathematical Sciences, Carnegie Mellon University, collaboratesWith, Department of Statistics and Data Science, Carnegie Mellon University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Department of Statistics and Data Science, Carnegie Mellon University
Context triple: [Department of Mathematical Sciences, Carnegie Mellon University, collaboratesWith, Department of Statistics and Data Science, Carnegie Mellon University]
  • A. Department of Statistics and Data Science chosen
    The Department of Statistics and Data Science is an academic unit specializing in statistical theory, data analysis, and computational methods within Carnegie Mellon University's Dietrich College of Humanities and Social Sciences.
  • B. Department of Statistical Science
    The Department of Statistical Science is an academic unit specializing in statistics and data analysis within a broader mathematical and physical sciences faculty.
  • C. Stanford University Department of Statistics
    The Stanford University Department of Statistics is a leading academic department renowned for its research and teaching in probability, statistics, and data science.
  • D. Centre for Statistics and Data Science
    The Centre for Statistics and Data Science is a research and methodological unit within the Norwegian Institute of Public Health that develops and applies advanced statistical and data science approaches to support public health research and decision-making.
  • E. Machine Learning Department, Carnegie Mellon University
    The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca827e50cc8190a92a733577184938 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae988bc2081909870bae1c2e9c238 completed March 30, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb14371e2081908d0a798d3b785c3c completed March 31, 2026, 12:24 a.m.
Created at: March 30, 2026, 4:33 p.m.