Triple

T7713106
Position Surface form Disambiguated ID Type / Status
Subject Pennsylvania State University E174809 entity
Predicate hasSchool P113 FINISHED
Object Dickinson Law E641088 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: Dickinson Law | Statement: [Pennsylvania State University, hasSchool, Dickinson Law]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dickinson Law
Context triple: [Pennsylvania State University, hasSchool, Dickinson Law]
  • A. Greenlaw
    Greenlaw is a small historic town in the Scottish Borders that once served as the county town of Berwickshire.
  • B. Franklin Pierce Law Center
    Franklin Pierce Law Center is a law school in New Hampshire known for its strong programs in intellectual property and patent law.
  • C. Notman Law
    Notman Law is a notable geographical feature located within the Tweedsmuir Hills of southern Scotland.
  • D. Dickinson School of Law chosen
    Dickinson School of Law is a historic American law school, now part of Pennsylvania State University, known for training generations of lawyers and public servants.
  • E. Langdell
    Langdell is a surname most notably associated with Christopher Columbus Langdell, the influential 19th-century dean of Harvard Law School who pioneered the case method of legal education.
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702c96e388190898165f84d646c0e completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acd3e9f88190adf42ab42c21b722 completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:04 p.m.