Triple
T19698959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vasavi Shakti |
E473039
|
entity |
| Predicate | lethalityScope |
P23477
|
FINISHED |
| Object | designed for a single chosen target |
—
|
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: designed for a single chosen target | Statement: [Vasavi Shakti, lethalityScope, designed for a single chosen target]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lethalityScope Context triple: [Vasavi Shakti, lethalityScope, designed for a single chosen target]
-
A.
lethality
Indicates the degree to which something is capable of causing death or fatal harm.
-
B.
casualtyRadius
Indicates the distance from a central point within which people or objects are likely to be harmed or killed by an event or action.
-
C.
canKill
Indicates that one entity has the ability or potential to cause the death of another entity.
-
D.
hazardScope
chosen
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
E.
effectOfDeath
Indicates the causal impact or consequences that a death has on another entity, state, or process.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b426608190a46abec3652a6ca0 |
completed | April 20, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.