Triple
T551236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariel Award |
E11843
|
entity |
| Predicate | hasCategory |
P87
|
FINISHED |
| Object |
Best Makeup
Best Makeup is a film industry award category recognizing outstanding achievement in makeup artistry.
|
E15718
|
NE FINISHED |
How this triple was built (4 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: Best Makeup | Statement: [Ariel Award, hasCategory, Best Makeup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Best Makeup Context triple: [Ariel Award, hasCategory, Best Makeup]
-
A.
Academy Award for Best Makeup and Hairstyling
The Academy Award for Best Makeup and Hairstyling is an Oscar category honoring outstanding achievement in makeup and hairstyling in film.
-
B.
COTY
COTY is the commonly used abbreviation for the National Basketball Association's Coach of the Year award.
-
C.
Maybelline New York
Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
-
D.
CoverGirl
CoverGirl is a major American cosmetics brand known for its mass-market makeup products and high-profile celebrity spokesmodels.
-
E.
Glamour Woman of the Year
Glamour Woman of the Year is an annual honor presented by Glamour magazine recognizing influential and inspiring women across various fields such as entertainment, politics, activism, and business.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Best Makeup Triple: [Ariel Award, hasCategory, Best Makeup]
Generated description
Best Makeup is a film industry award category recognizing outstanding achievement in makeup artistry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Best Makeup Target entity description: Best Makeup is a film industry award category recognizing outstanding achievement in makeup artistry.
-
A.
Academy Award for Best Makeup and Hairstyling
chosen
The Academy Award for Best Makeup and Hairstyling is an Oscar category honoring outstanding achievement in makeup and hairstyling in film.
-
B.
COTY
COTY is the commonly used abbreviation for the National Basketball Association's Coach of the Year award.
-
C.
Maybelline New York
Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
-
D.
CoverGirl
CoverGirl is a major American cosmetics brand known for its mass-market makeup products and high-profile celebrity spokesmodels.
-
E.
Glamour Woman of the Year
Glamour Woman of the Year is an annual honor presented by Glamour magazine recognizing influential and inspiring women across various fields such as entertainment, politics, activism, and business.
- F. None of above.
Provenance (5 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499030cf4819089b9163102255e49 |
completed | March 1, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4e0301ea08190ada81259b7c862f6 |
completed | March 2, 2026, 12:56 a.m. |
| NEDg | Description generation | batch_69a4e09ce7a48190b29e364be6317081 |
completed | March 2, 2026, 12:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4e10dc17881908399e10b705381cd |
completed | March 2, 2026, 12:59 a.m. |
Created at: March 1, 2026, 7:32 p.m.