Triple
T7177856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bush Doctrine |
E167364
|
entity |
| Predicate | focusesOnThreatType |
P19863
|
FINISHED |
| Object | weapons of mass destruction |
—
|
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: weapons of mass destruction | Statement: [Bush Doctrine, focusesOnThreatType, weapons of mass destruction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnThreatType Context triple: [Bush Doctrine, focusesOnThreatType, weapons of mass destruction]
-
A.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
B.
threatTypeAddressed
chosen
Indicates that a given action, measure, or entity is specifically intended to counter or mitigate a particular type of threat.
-
C.
threatType
Indicates the specific category or nature of a threat that one entity poses or represents in relation to another.
-
D.
threatTypeMonitored
Indicates that a particular type of threat is being actively observed, tracked, or watched for by some monitoring process or system.
-
E.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
- 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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.