Triple
T1934677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blu-ray Disc |
E41417
|
entity |
| Predicate | usesLaserColor |
P26637
|
FINISHED |
| Object | blue-violet |
—
|
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: blue-violet | Statement: [Blu-ray Disc, usesLaserColor, blue-violet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLaserColor Context triple: [Blu-ray Disc, usesLaserColor, blue-violet]
-
A.
usesLaserType
Indicates that one entity employs or operates a specific type or category of laser in performing an action or function.
-
B.
hasLaserShow
Indicates that an entity features or offers a laser-based visual show as part of its activities or attractions.
-
C.
hasColorPlay
Indicates a relationship where something exhibits or incorporates playful or varied use of color.
-
D.
rayColor
chosen
Indicates the specific color value associated with a given ray in a rendering or optical context.
-
E.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb29b51408190afb2f918814e68c7 |
completed | March 7, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69abaff07cf88190b4883c5f17f90abd |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.