Triple

T5392976
Position Surface form Disambiguated ID Type / Status
Subject University Professor at Boston University E120378 entity
Predicate tenureStatus P51579 FINISHED
Object typically tenured 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: typically tenured | Statement: [University Professor at Boston University, tenureStatus, typically tenured]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tenureStatus
Context triple: [University Professor at Boston University, tenureStatus, typically tenured]
  • A. tenureType
    Indicates the type or category of tenure or contractual engagement that characterizes the relationship between the involved entities.
  • B. tenureCharacteristic chosen
    Indicates a relationship where a specific attribute or quality characterizes the duration or conditions of someone’s or something’s tenure.
  • C. tenureDependsOn
    Indicates that the duration or continuation of one entity’s tenure is conditional on or determined by another specified factor or entity.
  • D. careerStatus
    Indicates the current stage, position, or condition of an entity within its professional or occupational life.
  • E. designationStatus
    Indicates the current official classification or standing assigned to an entity within a defined system or process.
  • 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_69bd46354c648190a38b26f107010a96 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd871b81d08190993928e2c6251226 completed March 20, 2026, 5:42 p.m.
PD Predicate disambiguation batch_69bd8463a9c88190bd760378f3026180 completed March 20, 2026, 5:31 p.m.
Created at: March 20, 2026, 2:04 p.m.