Triple

T9155611
Position Surface form Disambiguated ID Type / Status
Subject Xinhua News Agency E219699 entity
Predicate numberOfForeignBureaus P4564 FINISHED
Object over 170 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: over 170 | Statement: [Xinhua News Agency, numberOfForeignBureaus, over 170]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfForeignBureaus
Context triple: [Xinhua News Agency, numberOfForeignBureaus, over 170]
  • A. numberOfCountryOffices chosen
    Indicates the total count of offices or branches that an organization maintains across different countries.
  • B. hasDiplomaticMission
    Indicates that one entity maintains an official diplomatic representation, such as an embassy or mission, in the territory or jurisdiction of another entity.
  • C. numberOfBorderGuards
    Indicates the quantity of border guards associated with a given location, event, or entity.
  • D. hasConsularSection
    Indicates that an entity (typically a diplomatic mission or embassy) includes or is associated with a consular section responsible for consular services.
  • E. hasInternationalOrganizationOffice
    Indicates that an international organization maintains an official office or physical presence at a given location.
  • 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca9d274bc8190b734a814e253d18a completed April 1, 2026, 5:14 a.m.
PD Predicate disambiguation batch_69cc6605c6808190a30d92da006206ac completed April 1, 2026, 12:25 a.m.
Created at: March 30, 2026, 7:21 p.m.