Triple

T177341
Position Surface form Disambiguated ID Type / Status
Subject Harvard University Department of Government E3601 entity
Predicate offersCourseLevel P777 FINISHED
Object introductory courses in government LITERAL 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: introductory courses in government | Statement: [Harvard University Department of Government, offersCourseLevel, introductory courses in government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: offersCourseLevel
Context triple: [Harvard University Department of Government, offersCourseLevel, introductory courses in government]
  • A. offersDegree
    Indicates that an institution or program provides a specific academic degree as an available qualification.
  • B. offersProgramLevel chosen
    Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
  • C. trainingLevel
    Indicates the degree or stage of training or skill development that an entity has attained.
  • D. servesGradeLevels
    Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
  • E. offersFieldOfStudy
    Indicates that an institution or program provides a particular field of study as an available area of academic focus.
  • F. None of above.

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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a258fd278481908ad4498e03f38e2f completed Feb. 28, 2026, 2:54 a.m.
PD Predicate disambiguation batch_69a2566b53d481909c0ed40dd3719e8c completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:39 a.m.