Triple
T805542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merlin 1A |
E17423
|
entity |
| Predicate | gimbalCapability |
P21233
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Merlin 1A, gimbalCapability, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gimbalCapability Context triple: [Merlin 1A, gimbalCapability, yes]
-
A.
hasOpticalImageStabilization
Indicates that a device or component includes a feature that reduces image blur caused by camera movement during capture.
-
B.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
C.
gunStabilisation
Indicates that an entity performs or provides stabilization for a gun, reducing its movement or recoil to improve accuracy.
-
D.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
E.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ace369b481908ad69de6de99f5e6 |
completed | March 1, 2026, 9:17 p.m. |
Created at: March 1, 2026, 7:38 p.m.