Triple
T9000924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitsubishi Diamondtron |
E215035
|
entity |
| Predicate | displayTechnologyClass |
P82761
|
FINISHED |
| Object | analog display |
—
|
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: analog display | Statement: [Mitsubishi Diamondtron, displayTechnologyClass, analog display]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: displayTechnologyClass Context triple: [Mitsubishi Diamondtron, displayTechnologyClass, analog display]
-
A.
supportsDisplayTechnology
Indicates that one entity is compatible with, or capable of operating using, a specified display technology.
-
B.
technologyClass
chosen
Indicates the classification or category of technology to which an entity belongs.
-
C.
touchscreenType
Indicates the specific kind or technology of touchscreen associated with an entity.
-
D.
viewTechnology
Indicates that an entity observes, inspects, or examines a particular technology.
-
E.
technologicalFeature
Indicates that one entity possesses, exhibits, or is characterized by a specific technological capability, component, or functionality in relation to 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6954bb1881908d004a26ba7fe360 |
completed | April 1, 2026, 12:39 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.