Triple
T8573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Army Signal Corps |
E170
|
entity |
| Predicate | doctrineField |
P3
|
FINISHED |
| Object | signal operations |
—
|
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: signal operations | Statement: [United States Army Signal Corps, doctrineField, signal operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doctrineField Context triple: [United States Army Signal Corps, doctrineField, signal operations]
-
A.
excludesField
Indicates that one entity omits, leaves out, or does not include a particular field or attribute in its definition, usage, or scope.
-
B.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
C.
fieldOfWork
chosen
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
D.
foreignPolicyDoctrine
Indicates a state's overarching principles or strategic approach that guide its decisions and behavior in international relations.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.