Triple

T6605497
Position Surface form Disambiguated ID Type / Status
Subject Calimesa E149106 entity
Predicate locatedBetween P1262 FINISHED
Object Palm Springs E190789 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: Palm Springs | Statement: [Calimesa, locatedBetween, Palm Springs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palm Springs
Context triple: [Calimesa, locatedBetween, Palm Springs]
  • A. Palm Springs chosen
    Palm Springs is a desert resort city in Southern California known for its mid-century modern architecture, hot springs, golf courses, and tourism.
  • B. Palm Desert
    Palm Desert is a resort city in Southern California known for its golf courses, upscale shopping, and desert landscapes.
  • C. Rancho Mirage
    Rancho Mirage is an affluent resort city in Southern California known for its golf courses, luxury hotels, and desert climate.
  • D. Santa Ana
    Santa Ana is a major city in Orange County, California, known as a dense urban and governmental center within the Greater Los Angeles metropolitan area.
  • E. Santa Ana
    Santa Ana is a barangay (village-level administrative division) within the highly urbanized city of Taguig in Metro Manila, Philippines.
  • 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_69c687eaa7508190bb58ce2aa02039b3 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af13151c81909b68fa6c77e1c482 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eee3e2d08190b5cb503facf68818 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 1:56 p.m.