Triple
T32822227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department S |
E839463
|
entity |
| Predicate | intelligenceServiceType |
P175147
|
FINISHED |
| Object | foreign intelligence |
—
|
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: foreign intelligence | Statement: [Department S, intelligenceServiceType, foreign intelligence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intelligenceServiceType Context triple: [Department S, intelligenceServiceType, foreign intelligence]
-
A.
intelligenceService
Indicates that one entity functions as an intelligence or security service organization for another entity.
-
B.
intelligenceServiceDepicted
Indicates that an intelligence or security service organization is visually or narratively represented in the context (e.g., in a work, scene, or depiction).
-
C.
intelligenceUse
Indicates the use or application of intelligence by one entity toward a task, situation, or another entity.
-
D.
usesIntelligence
Indicates that an entity applies mental abilities such as reasoning, problem-solving, or understanding to perform an action or achieve a goal.
-
E.
typeOfIntelligence
Indicates that one entity is a specific kind or category of intelligence in relation to another entity.
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6ce6c76bc8190b865343d3f5810c9 |
completed | May 3, 2026, 4:26 a.m. |
Created at: May 1, 2026, 1:15 a.m.