Triple

T30424097
Position Surface form Disambiguated ID Type / Status
Subject Embassy of Guatemala in Moscow E773975 entity
Predicate hasMissionCategory P180722 FINISHED
Object bilateral embassy 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: bilateral embassy | Statement: [Embassy of Guatemala in Moscow, hasMissionCategory, bilateral embassy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMissionCategory
Context triple: [Embassy of Guatemala in Moscow, hasMissionCategory, bilateral embassy]
  • A. hasMissionIn
    Indicates that an entity carries out, undertakes, or is assigned a mission within a specified location or region.
  • B. hasMissionTo
    Indicates that an entity is assigned or dedicated to carrying out a specific mission, task, or purpose related to another entity or objective.
  • C. containsMission
    Indicates that one entity includes or encompasses a mission as part of its contents, scope, or responsibilities.
  • D. hasMissionSystem
    Indicates that an entity is equipped with or associated with a specific mission-related system or subsystem.
  • E. hasMissionActivity
    Indicates that an entity is associated with, performs, or is involved in a specific mission-related activity.
  • F. None of above. chosen

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_69f22491ba248190b9a4776ca8e42d02 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f74c70fd248190a9d5543afcb08211 completed May 3, 2026, 1:24 p.m.
PD Predicate disambiguation batch_69f7478e3b548190a51d5d436e2bb036 completed May 3, 2026, 1:03 p.m.
PDg Predicate description generation batch_69f74c6fa6548190b03935f65429a24e completed May 3, 2026, 1:23 p.m.
Created at: April 29, 2026, 8:06 p.m.