Triple
T12922775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FASGW(H) anti-ship missiles |
E309164
|
entity |
| Predicate | targetSet |
P860
|
FINISHED |
| Object | littoral surface threats |
—
|
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: littoral surface threats | Statement: [FASGW(H) anti-ship missiles, targetSet, littoral surface threats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetSet Context triple: [FASGW(H) anti-ship missiles, targetSet, littoral surface threats]
-
A.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
B.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
C.
target
chosen
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
D.
targetWork
Indicates that one entity is the specific work (e.g., document, artwork, or project) that another entity is directed at, refers to, or is primarily concerned with.
-
E.
targetsSystems
Indicates that an entity is directed at, attacks, or is intended to affect specific systems.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971e9576c81908eb59569af6da877 |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.