Triple

T36803672
Position Surface form Disambiguated ID Type / Status
Subject United States–Montenegro relations E909386 entity
Predicate supportedReformsIn P194061 FINISHED
Object rule of law in Montenegro 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: rule of law in Montenegro | Statement: [United States–Montenegro relations, supportedReformsIn, rule of law in Montenegro]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: supportedReformsIn
Context triple: [United States–Montenegro relations, supportedReformsIn, rule of law in Montenegro]
  • A. supportsReformType chosen
    Indicates that one entity endorses, advocates for, or is in favor of a particular type or category of reform associated with another entity.
  • B. supportedReformer
    Indicates that one entity actively endorsed or backed a particular reformer in their efforts or cause.
  • C. reformsBy
    Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
  • D. implementedReformsIn
    Indicates that an entity (typically a person, organization, or government) carried out or put into effect specific reforms within a particular context, domain, or location.
  • E. associatedReforms
    Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
  • 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_69f76e7b98888190899b6478a82ad6ae completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a037c8e2c648190a65fc9c7872861af completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a037a0e039481908a4a2666f76c5363 completed May 12, 2026, 7:05 p.m.
Created at: May 3, 2026, 4:12 p.m.