Triple

T1732981
Position Surface form Disambiguated ID Type / Status
Subject U.S. Forces Japan E37853 entity
Predicate typeOfPresence P31835 FINISHED
Object forward-deployed force 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: forward-deployed force | Statement: [U.S. Forces Japan, typeOfPresence, forward-deployed force]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfPresence
Context triple: [U.S. Forces Japan, typeOfPresence, forward-deployed force]
  • A. hasHumanPresence
    Indicates that humans are physically present in or occupying a given location, object, or context.
  • B. globalPresence
    Indicates that an entity operates, is represented, or has a significant footprint across multiple countries or world regions.
  • C. fieldPresence
    Indicates that a particular field or attribute exists or is present within a given context, object, or dataset.
  • D. onlinePresence
    Indicates that an entity maintains a presence or representation on the internet, such as through websites, profiles, or digital platforms.
  • E. mediaPresence
    Indicates the extent to which something is visible, represented, or covered within various media channels or platforms.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab5c553e508190b0f511b05e07fa20 completed March 6, 2026, 10:59 p.m.
PD Predicate disambiguation batch_69aa61c25a648190892de94c997fb983 completed March 6, 2026, 5:10 a.m.
PDg Predicate description generation batch_69ab5c54362881908895ab249cad8c1d completed March 6, 2026, 10:59 p.m.
Created at: March 4, 2026, 7:30 p.m.