Triple

T1951072
Position Surface form Disambiguated ID Type / Status
Subject 4th Psychological Operations Group (Airborne) E42156 entity
Predicate languageCapability P29822 FINISHED
Object multiple foreign languages 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: multiple foreign languages | Statement: [4th Psychological Operations Group (Airborne), languageCapability, multiple foreign languages]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageCapability
Context triple: [4th Psychological Operations Group (Airborne), languageCapability, multiple foreign languages]
  • A. languageFeature
    Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
  • B. languageCapacity chosen
    Indicates the extent to which an entity is able to understand, produce, or otherwise use language.
  • C. languageProvision
    Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
  • D. hasLanguageModel
    Indicates that an entity possesses, uses, or is associated with a particular language model.
  • E. languageOfOperation
    Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb34d94fc8190a5bf1e582c77c725 completed March 7, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69abaff3eda88190b643994cb4dfb8df completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:36 p.m.