Triple
T8427623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sia |
E199040
|
entity |
| Predicate | knownForVisualTrademark |
P14764
|
FINISHED |
| Object | face-covering two-tone wig |
—
|
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: face-covering two-tone wig | Statement: [Sia, knownForVisualTrademark, face-covering two-tone wig]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForVisualTrademark Context triple: [Sia, knownForVisualTrademark, face-covering two-tone wig]
-
A.
visualTrademark
Indicates that one entity serves as a visual trademark or logo representing another entity.
-
B.
trademark
Indicates that one entity legally owns and uses a distinctive sign, name, or symbol to identify and distinguish its goods or services from those of others.
-
C.
hasBrandRecognitionFor
Indicates that one entity is aware of, recognizes, or can identify the brand of another entity.
-
D.
brandingFeature
chosen
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
E.
recognizedFor
Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:07 p.m.