Triple

T993143
Position Surface form Disambiguated ID Type / Status
Subject San Diego Zoo Safari Park E21434 entity
Predicate typeOfAttraction P8077 FINISHED
Object outdoor attraction LITERAL 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: outdoor attraction | Statement: [San Diego Zoo Safari Park, typeOfAttraction, outdoor attraction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfAttraction
Context triple: [San Diego Zoo Safari Park, typeOfAttraction, outdoor attraction]
  • A. attractionType chosen
    Indicates the specific kind or category of attraction that characterizes the relationship between entities.
  • B. isMajorAttractionFor
    Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
  • C. isAttractionFor
    Indicates that one entity serves as an attraction or point of interest specifically intended for another entity (such as a person, group, or audience).
  • D. containsAttraction
    Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
  • E. hasAttractionType
    Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
  • F. None of above.

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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4c3f7b48190a31308bdc09817c6 completed March 1, 2026, 9:51 p.m.
PD Predicate disambiguation batch_69a4b2adbde48190b07966d0c3179516 completed March 1, 2026, 9:42 p.m.
Created at: March 1, 2026, 7:41 p.m.