Triple
T31792591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Navy anti-submarine squadrons |
E811509
|
entity |
| Predicate | typicalSensor |
P17204
|
FINISHED |
| Object | airborne radar |
—
|
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: airborne radar | Statement: [U.S. Navy anti-submarine squadrons, typicalSensor, airborne radar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSensor Context triple: [U.S. Navy anti-submarine squadrons, typicalSensor, airborne radar]
-
A.
hasSensor
chosen
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
B.
sensorClass
Indicates that one entity is classified as a type or category of sensor relative to another entity.
-
C.
trackingSensor
Indicates that a sensor is monitoring, recording, or following the state, position, or behavior of a target entity over time.
-
D.
basicSense
Indicates that one entity represents the most fundamental or primary meaning or interpretation of another entity.
-
E.
sensorTypesInvolved
Indicates the types of sensors that participate in or are utilized within a given event, process, or system.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 11:39 p.m.