Triple
T30357524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hi-MD |
E772187
|
entity |
| Predicate | opticalTechnology |
P169091
|
FINISHED |
| Object | laser-based read/write |
—
|
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: laser-based read/write | Statement: [Hi-MD, opticalTechnology, laser-based read/write]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opticalTechnology Context triple: [Hi-MD, opticalTechnology, laser-based read/write]
-
A.
hasOpticalElement
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
-
B.
visualTechnology
Indicates a relationship where one entity is a technology used to capture, process, display, or otherwise handle visual information for another entity or context.
-
C.
cameraTechnology
Indicates the type or characteristics of camera-related technology associated with an entity.
-
D.
opticalDesign
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
-
E.
hasOpticalChannels
Indicates that an entity possesses one or more optical communication or signal-transmission channels.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6823fe8c48190a8911627f79dd949 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:57 p.m.