Triple

T644918
Position Surface form Disambiguated ID Type / Status
Subject Saint Louis Zoo E11219 entity
Predicate hasParkingPolicy P3380 FINISHED
Object paid parking lots with limited street parking nearby 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: paid parking lots with limited street parking nearby | Statement: [Saint Louis Zoo, hasParkingPolicy, paid parking lots with limited street parking nearby]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasParkingPolicy
Context triple: [Saint Louis Zoo, hasParkingPolicy, paid parking lots with limited street parking nearby]
  • A. hasParking
    Indicates that a place or facility provides designated parking space(s) available for use.
  • B. parkingType chosen
    Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
  • C. hasReservationPolicy
    Indicates that an entity specifies or is governed by a particular policy regarding how reservations are made, managed, or honored.
  • D. parkSection
    Indicates a relationship where a specific area or subsection belongs to, is contained within, or is designated as part of a larger park.
  • E. hasParkDistrict
    Indicates that an entity is associated with, located within, or administered by a specific park district.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f19f9a08190b0bf6e19b32427ff completed March 1, 2026, 8:18 p.m.
PD Predicate disambiguation batch_69a49d0a0ab481909871461418a00be7 completed March 1, 2026, 8:09 p.m.
Created at: March 1, 2026, 7:36 p.m.