Triple

T8068067
Position Surface form Disambiguated ID Type / Status
Subject Oceanside Pier E188294 entity
Predicate city P40 FINISHED
Object Oceanside E36088 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: Oceanside | Statement: [Oceanside Pier, city, Oceanside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oceanside
Context triple: [Oceanside Pier, city, Oceanside]
  • A. Oceanside chosen
    Oceanside is a coastal city in northern San Diego County known for its beaches, historic wooden pier, and laid-back Southern California surf culture.
  • B. Oceanside
    Oceanside is a suburban hamlet in Nassau County, Long Island, New York, known as a residential community near the South Shore waterfront.
  • C. Imperial Beach
    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.
  • D. Carpinteria
    Carpinteria is a small coastal city in Southern California known for its beaches, laid-back atmosphere, and annual avocado festival.
  • E. Laguna Beach
    Laguna Beach is a coastal Southern California city renowned for its scenic beaches, vibrant arts community, and historic role as a hub for the California Impressionist art movement.
  • 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff8a4fc8190a97fc7111ca7ec4d completed March 31, 2026, 3:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce4d5b80b48190909ca7775fda2ed9 completed April 2, 2026, 11:04 a.m.
Created at: March 30, 2026, 5:27 p.m.