Triple
T1170634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany Blue |
E24902
|
entity |
| Predicate | isProtectedAs |
P7647
|
FINISHED |
| Object | trade dress |
—
|
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: trade dress | Statement: [Tiffany Blue, isProtectedAs, trade dress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isProtectedAs Context triple: [Tiffany Blue, isProtectedAs, trade dress]
-
A.
isProtectedFor
Indicates that one entity is safeguarded or preserved specifically for the benefit, use, or rights of another entity.
-
B.
isProtectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
C.
protectedAs
chosen
Indicates that one entity is safeguarded, preserved, or kept safe by another entity or under a specified protective status or mechanism.
-
D.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
E.
protectedFor
Indicates that something is safeguarded or preserved specifically for the benefit, use, or rights of a particular entity or purpose.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce972cc8190bce0b77cfda6da41 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.