Triple
T10683435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kellogg Company |
E251813
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
All-Bran
All-Bran is a high-fiber breakfast cereal produced by Kellogg’s, marketed primarily for its digestive and heart health benefits.
|
E878380
|
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: All-Bran | Statement: [Kellogg Company, brand, All-Bran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: All-Bran Context triple: [Kellogg Company, brand, All-Bran]
-
A.
Fibra Uno
Fibra Uno is a major Mexican real estate investment trust (FIBRA) that owns and operates a large portfolio of commercial properties across Mexico.
-
B.
Crispi
Crispi is an Italian surname most notably associated with Francesco Crispi, a prominent 19th-century Italian statesman and former Prime Minister.
-
C.
Rice Krispies
Rice Krispies is a novelty song best known for its playful, percussive use of cereal sounds and humorous approach to everyday breakfast.
-
D.
Bulgur
Bulgur is a whole grain food made from cracked, parboiled wheat, commonly used in Middle Eastern and Mediterranean dishes like pilafs, salads, and stuffings.
-
E.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
- 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: All-Bran Triple: [Kellogg Company, brand, All-Bran]
Generated description
All-Bran is a high-fiber breakfast cereal produced by Kellogg’s, marketed primarily for its digestive and heart health benefits.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: All-Bran Target entity description: All-Bran is a high-fiber breakfast cereal produced by Kellogg’s, marketed primarily for its digestive and heart health benefits.
-
A.
Fibra Uno
Fibra Uno is a major Mexican real estate investment trust (FIBRA) that owns and operates a large portfolio of commercial properties across Mexico.
-
B.
Crispi
Crispi is an Italian surname most notably associated with Francesco Crispi, a prominent 19th-century Italian statesman and former Prime Minister.
-
C.
Rice Krispies
Rice Krispies is a novelty song best known for its playful, percussive use of cereal sounds and humorous approach to everyday breakfast.
-
D.
Bulgur
Bulgur is a whole grain food made from cracked, parboiled wheat, commonly used in Middle Eastern and Mediterranean dishes like pilafs, salads, and stuffings.
-
E.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fcc43b9481908f35490db93db76c |
completed | April 9, 2026, 1:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9888cf7b481909de6a4fecb48cf4b |
completed | April 10, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69d98aea391c81909ec64a29053c35c1 |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98c04e8c08190b4d7bc63357c69f4 |
completed | April 10, 2026, 11:47 p.m. |
Created at: April 8, 2026, 9:10 p.m.