Triple
T24995611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P-12 early warning radar |
E625558
|
entity |
| Predicate | emitterType |
P46939
|
FINISHED |
| Object | active radar transmitter |
—
|
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: active radar transmitter | Statement: [P-12 early warning radar, emitterType, active radar transmitter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emitterType Context triple: [P-12 early warning radar, emitterType, active radar transmitter]
-
A.
emissionType
chosen
Indicates the specific category or kind of emission associated with an entity or activity.
-
B.
transmitterType
Indicates the kind or category of transmitter associated with or used by an entity.
-
C.
eraType
Indicates the classification of a time period or era according to its type or category.
-
D.
ejectorType
Indicates the specific kind or category of ejector mechanism associated with an entity or system.
-
E.
broadcasterType
Indicates the category or kind of broadcaster involved in the relationship or action (e.g., public, commercial, online).
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44a4a2c048190bfb5afe6df7ca3f0 |
completed | May 1, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:04 a.m.