Triple
T16629503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbott family |
E404038
|
entity |
| Predicate | associatedWithCompany |
P629
|
FINISHED |
| Object | Jabot Cosmetics |
E1225126
|
NE 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: Jabot Cosmetics | Statement: [Abbott family, associatedWithCompany, Jabot Cosmetics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jabot Cosmetics Context triple: [Abbott family, associatedWithCompany, Jabot Cosmetics]
-
A.
Jabot Cosmetics
chosen
Jabot Cosmetics is a prominent fictional beauty and skincare company featured in the long-running soap opera "The Young and the Restless."
-
B.
Kylie Cosmetics
Kylie Cosmetics is a makeup and beauty brand founded by Kylie Jenner, known for its trend-setting lip kits and social media–driven marketing.
-
C.
Iman Cosmetics
Iman Cosmetics is a beauty brand founded by supermodel Iman, known for pioneering makeup products designed specifically for women of color.
-
D.
Too Faced
Too Faced is a popular cosmetics brand known for its playful, feminine packaging and trend-driven makeup products.
-
E.
Huda Beauty
Huda Beauty is a globally popular cosmetics brand founded by makeup artist and influencer Huda Kattan, known for its trend-setting makeup products and strong social media presence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e4db5081908a6085f1bc2d65b8 |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084b7b94481909dfc0dd7b009a5b4 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 5:17 a.m.