Triple
T35624019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrocolor |
E1029397
|
entity |
| Predicate | colorProcessBranding |
P184062
|
FINISHED |
| Object | MGM trade name |
—
|
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: MGM trade name | Statement: [Metrocolor, colorProcessBranding, MGM trade name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorProcessBranding Context triple: [Metrocolor, colorProcessBranding, MGM trade name]
-
A.
colorTreatment
Indicates that an entity has undergone a process or action that changes, enhances, or assigns its color.
-
B.
serviceBrandColor
Indicates the association between a service and the color used to represent its brand identity.
-
C.
colorTincture
Indicates that one entity has a specific heraldic color or tincture applied to it.
-
D.
bannerColor
Indicates the color associated with a banner in the relationship or context described.
-
E.
colorUse
Indicates that one entity uses, applies, or is associated with a particular color in its appearance, design, or representation.
- 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:05 p.m.