Triple

T13757218
Position Surface form Disambiguated ID Type / Status
Subject Basketball Wives E330505 entity
Predicate laterSetIn P64727 FINISHED
Object Los Angeles E715 NE FINISHED

How this triple was built (3 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: Los Angeles | Statement: [Basketball Wives, laterSetIn, Los Angeles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Los Angeles
Context triple: [Basketball Wives, laterSetIn, Los Angeles]
  • A. Los Angeles chosen
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • B. Los Ángeles
    Los Ángeles is a mid-sized Chilean city known as an important commercial and agricultural center in the south-central part of the country.
  • C. San Angeles
    San Angeles is a fictional futuristic megacity formed from the merger of Los Angeles and San Diego in the science fiction film "Demolition Man."
  • D. San Fransokyo
    San Fransokyo is a fictional futuristic hybrid city combining elements of San Francisco and Tokyo, serving as the primary setting of Disney's animated film "Big Hero 6."
  • E. Santa Monica
    Santa Monica is a coastal city in western Los Angeles County, California, known for its iconic pier, beaches, and vibrant tourism and entertainment scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: laterSetIn
Context triple: [Basketball Wives, laterSetIn, Los Angeles]
  • A. laterIn
    Indicates that one event, state, or time point occurs after another in temporal order.
  • B. laterWithin
    Indicates that one event or time point occurs later than another while still falling within a specified temporal interval or boundary.
  • C. laterWrittenDownIn
    Indicates that information, events, or content were recorded or documented at a later time than when they originally occurred or were created.
  • D. basedInLater chosen
    Indicates that an entity is located or headquartered in a place during a later time period or phase, relative to some earlier location or state.
  • E. laterDeployedIn
    Indicates that one entity was deployed or put into operation in a particular context, location, or system at a later time than another.
  • F. None of above.

Provenance (4 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de022286b481908f8a801042743512 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8cebcd481909ba75eef518b34c7 completed May 3, 2026, 9:06 p.m.
PD Predicate disambiguation batch_69dbbe97846c819093b00ea117b64e0d completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 10:09 p.m.