Triple

T8512663
Position Surface form Disambiguated ID Type / Status
Subject Coronado Island E201494 entity
Predicate near P350 FINISHED
Object Imperial Beach E201776 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: Imperial Beach | Statement: [Coronado Island, near, Imperial Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imperial Beach
Context triple: [Coronado Island, near, Imperial Beach]
  • A. Imperial Beach chosen
    Imperial Beach is a small coastal city in Southern California known for its sandy beaches, surfing culture, and location at the southern end of the San Diego Bay near the U.S.–Mexico border.
  • B. Hermosa Beach
    Hermosa Beach is a coastal city in Los Angeles County known for its sandy beaches, surf culture, and vibrant beachfront community.
  • C. Oceanside
    Oceanside is a coastal city in northern San Diego County known for its beaches, historic wooden pier, and laid-back Southern California surf culture.
  • D. Oceanside
    Oceanside is a suburban hamlet in Nassau County, Long Island, New York, known as a residential community near the South Shore waterfront.
  • E. Rosarito Beach
    Rosarito Beach is a popular coastal resort area in Baja California, Mexico, known for its sandy beaches, nightlife, and proximity to the U.S. border.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60b0d4c8190812ddbc1c17389c8 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69d046efb42c8190b19c8ecd5efa8956 completed April 3, 2026, 11:02 p.m.
Created at: March 30, 2026, 6:15 p.m.