Triple

T3995284
Position Surface form Disambiguated ID Type / Status
Subject Professor at Massachusetts Institute of Technology E87083 entity
Predicate tenureEligibility P84 FINISHED
Object tenure-track 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: tenure-track | Statement: [Professor at Massachusetts Institute of Technology, tenureEligibility, tenure-track]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tenureEligibility
Context triple: [Professor at Massachusetts Institute of Technology, tenureEligibility, tenure-track]
  • A. tenureType
    Indicates the type or category of tenure or contractual engagement that characterizes the relationship between the involved entities.
  • B. tenureCharacteristic
    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. eligibility chosen
    Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
  • E. endOfTenure
    Indicates the point or event at which an entity’s period of holding a role, position, or office concludes.
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb81040481909b22e4c445ecae0f completed March 9, 2026, 4:55 p.m.
PD Predicate disambiguation batch_69aef8f692008190bf4d637ffc3d3eaa completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:34 p.m.