Triple
T14373188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make Up For Ever |
E356405
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object |
Aqua Seal
Aqua Seal is a popular Make Up For Ever mixing medium that transforms powders and pigments into long-lasting, waterproof formulas.
|
E1095596
|
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: Aqua Seal | Statement: [Make Up For Ever, notableProduct, Aqua Seal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aqua Seal Context triple: [Make Up For Ever, notableProduct, Aqua Seal]
-
A.
Rainmaster
Rainmaster was the famous nickname of German racing driver Rudolf Caracciola, renowned for his exceptional skill in wet-weather Grand Prix conditions.
-
B.
LouSeal
LouSeal is the playful seal mascot of the Columbus Clippers minor league baseball team, entertaining fans at games in Columbus, Ohio.
-
C.
Aquatica
Aquatica is a chain of water parks owned and operated by SeaWorld Parks & Entertainment, known for combining high-thrill water attractions with marine life themes.
-
D.
Aquata
Aquata is one of King Triton’s mermaid daughters and a princess of Atlantica in Disney’s The Little Mermaid franchise.
-
E.
Waterman
Waterman is a historic luxury pen and writing instruments brand known for its high-quality fountain pens and elegant design.
- 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: Aqua Seal Triple: [Make Up For Ever, notableProduct, Aqua Seal]
Generated description
Aqua Seal is a popular Make Up For Ever mixing medium that transforms powders and pigments into long-lasting, waterproof formulas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aqua Seal Target entity description: Aqua Seal is a popular Make Up For Ever mixing medium that transforms powders and pigments into long-lasting, waterproof formulas.
-
A.
Rainmaster
Rainmaster was the famous nickname of German racing driver Rudolf Caracciola, renowned for his exceptional skill in wet-weather Grand Prix conditions.
-
B.
LouSeal
LouSeal is the playful seal mascot of the Columbus Clippers minor league baseball team, entertaining fans at games in Columbus, Ohio.
-
C.
Aquatica
Aquatica is a chain of water parks owned and operated by SeaWorld Parks & Entertainment, known for combining high-thrill water attractions with marine life themes.
-
D.
Aquata
Aquata is one of King Triton’s mermaid daughters and a princess of Atlantica in Disney’s The Little Mermaid franchise.
-
E.
Waterman
Waterman is a historic luxury pen and writing instruments brand known for its high-quality fountain pens and elegant design.
- F. None of above. chosen
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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c5514688190be90776c8764d4f3 |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd4d56b67c8190bc9ecd4f444df780 |
completed | May 8, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4e9a678c8190bd1821e6c43a3a1a |
completed | May 8, 2026, 2:46 a.m. |
Created at: April 10, 2026, 1:15 a.m.