Triple
T35790753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tic Tac (UFO) |
E1034684
|
entity |
| Predicate | sensorTypesInvolved |
P184110
|
FINISHED |
| Object | 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: radar | Statement: [Tic Tac (UFO), sensorTypesInvolved, radar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensorTypesInvolved Context triple: [Tic Tac (UFO), sensorTypesInvolved, radar]
-
A.
sensorTypesPermitted
Indicates that certain types or categories of sensors are allowed or authorized for use in a given context or configuration.
-
B.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
-
C.
sensorClass
Indicates that one entity is classified as a type or category of sensor relative to another entity.
-
D.
hasSensor
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
E.
sensorArchitecture
Indicates the structural design or configuration of a sensor system, including how its components are organized and interact to perform sensing functions.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.