Triple
T6472701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ground-based Midcourse Defense |
E145992
|
entity |
| Predicate | killMechanism |
P71002
|
FINISHED |
| Object | hit-to-kill kinetic interception |
—
|
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: hit-to-kill kinetic interception | Statement: [Ground-based Midcourse Defense, killMechanism, hit-to-kill kinetic interception]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killMechanism Context triple: [Ground-based Midcourse Defense, killMechanism, hit-to-kill kinetic interception]
-
A.
deathMethod
Indicates the specific way or means by which a death occurred.
-
B.
willKill
Indicates that one entity is destined or intends to cause the death of another entity in the future.
-
C.
killedBy
Indicates that one entity caused the death of another entity.
-
D.
usedMethodOfKilling
Indicates that one entity employed a particular method or means to carry out a killing of another entity.
-
E.
attemptedToKill
Indicates that one entity took deliberate action with the intention of causing the death of another entity, regardless of whether the death actually occurred.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a3188488190a1b7452ede91ba5e |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067da970481908a038995ba7dfb4b |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:50 p.m.