Triple
T18338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Containment |
E362
|
entity |
| Predicate | relatedDoctrine |
P436
|
FINISHED |
| Object | domino theory |
—
|
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: domino theory | Statement: [Containment, relatedDoctrine, domino theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedDoctrine Context triple: [Containment, relatedDoctrine, domino theory]
-
A.
foreignPolicyDoctrine
chosen
Indicates a state's overarching principles or strategic approach that guide its decisions and behavior in international relations.
-
B.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
D.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
E.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246cbca108190a92478df126d9bf8 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a2464f61648190ac690044be194972 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.