Triple
T9594212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sea Gnat decoy system |
E231489
|
entity |
| Predicate | decoyType |
P89119
|
FINISHED |
| Object | radar-reflective decoy |
—
|
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: radar-reflective decoy | Statement: [Sea Gnat decoy system, decoyType, radar-reflective decoy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decoyType Context triple: [Sea Gnat decoy system, decoyType, radar-reflective decoy]
-
A.
typeOfDecoration
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
-
B.
hasDecoySystem
Indicates that an entity is equipped with or employs a decoy system designed to mislead, distract, or confuse another entity or process.
-
C.
disguisedAs
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
D.
isCombatDecoration
Indicates that an award or decoration is specifically given for participation or valor in combat or military conflict.
-
E.
isNonCombatDecoration
Indicates that an award or decoration is given for non-combat service or achievements rather than for participation in direct combat.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a134b0c81908a568e5d2ecfbb92 |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:07 p.m.