Triple

T2489436
Position Surface form Disambiguated ID Type / Status
Subject King George Street, Jerusalem E52003 entity
Predicate hasGovernmentOfficesNearby P12057 FINISHED
Object yes 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: yes | Statement: [King George Street, Jerusalem, hasGovernmentOfficesNearby, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGovernmentOfficesNearby
Context triple: [King George Street, Jerusalem, hasGovernmentOfficesNearby, yes]
  • A. governingBodyNearby chosen
    Indicates that a governing body is located in close physical proximity to the referenced entity or area.
  • B. isGovernmentFacility
    Indicates that the subject entity functions as a facility owned, operated, or officially designated for use by a government or its agencies.
  • C. nearbyFederalAgency
    Indicates that one federal agency is located geographically close to another federal agency.
  • D. headquartersNeighborhood
    Indicates that an organization’s main headquarters is located within a specific neighborhood.
  • E. hostGovernment
    Indicates that a government serves as the official host or primary responsible authority for an event, activity, organization, or foreign presence within its jurisdiction.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd17b7a048190bcc8f0a66514a052 completed March 7, 2026, 7:19 a.m.
PD Predicate disambiguation batch_69abd0b980b481908d4932bcea4a6167 completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:45 p.m.