Triple

T5337677
Position Surface form Disambiguated ID Type / Status
Subject Bel Air E123864 entity
Predicate hasLandmark P105 FINISHED
Object Hotel Bel-Air E394428 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: Hotel Bel-Air | Statement: [Bel Air, hasLandmark, Hotel Bel-Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hotel Bel-Air
Context triple: [Bel Air, hasLandmark, Hotel Bel-Air]
  • A. Hotel Bel-Air chosen
    Hotel Bel-Air is a historic, ultra-luxury hotel in Los Angeles known for its secluded garden setting, celebrity clientele, and classic Hollywood glamour.
  • B. Bel-Air
    Bel-Air is a Paris Métro station located in the 12th arrondissement of Paris, France.
  • C. Bel-Air
    Bel-Air is a central public transport interchange in Geneva, Switzerland, serving as a key node for tram and bus connections across the city.
  • D. Bel-Air
    Bel-Air is an upscale residential and commercial barangay in Makati City, Metro Manila, known for its gated villages and proximity to the central business district.
  • E. Topridge
    Topridge is a historic Adirondack Great Camp in New York, renowned as a lavish wilderness retreat built in the early 20th century for socialite Marjorie Merriweather Post.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c6ec008190ad7a8a54360387d8 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c54ca4819095ca1d81ee061937 completed March 21, 2026, 10:16 p.m.
Created at: March 20, 2026, 2 p.m.