Triple
T4135912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sparkle |
E85153
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Brawny |
E85152
|
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: Brawny | Statement: [Sparkle, competesWith, Brawny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brawny Context triple: [Sparkle, competesWith, Brawny]
-
A.
Brawny
chosen
Brawny is a popular American paper towel brand known for its strong, absorbent products and its iconic lumberjack-themed packaging.
-
B.
Charmin
Charmin is a popular brand of toilet paper known for its softness and comfort, produced by Procter & Gamble.
-
C.
K/O Paper Products
K/O Paper Products is a television and film production company best known for developing genre and science-fiction projects, including the TV series "Sleepy Hollow."
-
D.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
E.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0233009881909333375d597b58b6 |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f2bb38c819090884069688063d2 |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.