Triple

T842579
Position Surface form Disambiguated ID Type / Status
Subject Phoenix metropolitan area E18208 entity
Predicate containsCity P294 FINISHED
Object Mesa, Arizona E19620 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: Mesa, Arizona | Statement: [Phoenix metropolitan area, containsCity, Mesa, Arizona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mesa, Arizona
Context triple: [Phoenix metropolitan area, containsCity, Mesa, Arizona]
  • A. Mesa, Arizona chosen
    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.
  • B. 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.
  • C. Scottsdale, Arizona
    Scottsdale, Arizona is a resort city in the Sonoran Desert near Phoenix, known for its upscale tourism, golf courses, and vibrant arts and nightlife scenes.
  • D. Flagstaff
    Flagstaff is a high-elevation city in northern Arizona known for its proximity to the Grand Canyon, its historic Route 66 corridor, and its role as a center for astronomy and outdoor recreation.
  • E. Mesa
    Mesa is a pioneering systems programming language developed at Xerox PARC in the 1970s, notable for its strong typing, modularity, and influence on later languages and operating system design.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe8a0bc81909b54af465e67be1f completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a93398a6948190981e932178aee6b9 completed March 5, 2026, 7:41 a.m.
Created at: March 1, 2026, 7:38 p.m.