Triple
T9538057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuttle Imaging Radar-B |
E230069
|
entity |
| Predicate | imagingMode |
P52562
|
FINISHED |
| Object | side-looking 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: side-looking radar | Statement: [Shuttle Imaging Radar-B, imagingMode, side-looking radar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imagingMode Context triple: [Shuttle Imaging Radar-B, imagingMode, side-looking radar]
-
A.
exposureModes
Indicates the different ways or conditions under which an entity can be exposed to another entity, factor, or influence.
-
B.
hasImagingType
chosen
Indicates the specific imaging modality or technique associated with or used in a given imaging procedure or result.
-
C.
displayMode
Indicates how content or information is visually presented or arranged to the user.
-
D.
imageQuality
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
E.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98cfead8819089a8f47ea83500a4 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.