Triple

T386798
Position Surface form Disambiguated ID Type / Status
Subject University of Chicago E8795 entity
Predicate hasMascot P52 FINISHED
Object Phoenix E9582 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: Phoenix | Statement: [University of Chicago, hasMascot, Phoenix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phoenix
Context triple: [University of Chicago, hasMascot, Phoenix]
  • A. Phoenix chosen
    Phoenix is the capital and largest city of the U.S. state of Arizona, known for its desert climate, rapid growth, and role as a major economic and cultural center in the American Southwest.
  • B. Mesa, Arizona
    Mesa, Arizona is a large city in the Phoenix metropolitan area known for its desert climate, suburban communities, and role as a major spring training hub for Major League Baseball.
  • C. Tucson
    Tucson is a major city in southern Arizona known for its desert landscape, rich Native American and Mexican cultural influences, and the University of Arizona.
  • D. PHX
    PHX is the three-letter FAA airport code for Phoenix Sky Harbor International Airport, the primary commercial airport serving the Phoenix, Arizona metropolitan area.
  • E. Tempe
    Tempe is a city in the Phoenix metropolitan area of Arizona, known for being home to Arizona State University and its vibrant college-town atmosphere.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec447b5481908a5a084787b44ced completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b44959c8190a793b4e5af838c7c completed March 1, 2026, 10:56 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.