Triple
T7113410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altria Group |
E165757
|
entity |
| Predicate | brandPortfolioIncludes |
P18121
|
FINISHED |
| Object |
Skoal
Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
|
E642851
|
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: Skoal | Statement: [Altria Group, brandPortfolioIncludes, Skoal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skoal Context triple: [Altria Group, brandPortfolioIncludes, Skoal]
-
A.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
B.
Lemonal
Lemonal is a small rural village in Belize known for its traditional Creole community and proximity to wetlands and wildlife.
-
C.
Opekta
Opekta was a German-Dutch company that produced and sold pectin-based gelling agents for making jam, notably managed in its Amsterdam branch by Anne Frank’s father, Otto Frank.
-
D.
Looz
Looz is the historical name of the medieval County of Loon, a former principality in what is now eastern Belgium.
-
E.
Axe
Axe is a popular men’s grooming brand known for its deodorants, body sprays, and personal care products marketed with a youthful, edgy image.
- 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: Skoal Triple: [Altria Group, brandPortfolioIncludes, Skoal]
Generated description
Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skoal Target entity description: Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
-
A.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
-
B.
Lemonal
Lemonal is a small rural village in Belize known for its traditional Creole community and proximity to wetlands and wildlife.
-
C.
Opekta
Opekta was a German-Dutch company that produced and sold pectin-based gelling agents for making jam, notably managed in its Amsterdam branch by Anne Frank’s father, Otto Frank.
-
D.
Looz
Looz is the historical name of the medieval County of Loon, a former principality in what is now eastern Belgium.
-
E.
Axe
Axe is a popular men’s grooming brand known for its deodorants, body sprays, and personal care products marketed with a youthful, edgy image.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5ef813c8190bec0ab0cbae430e5 |
completed | March 27, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cbc35d48190974e207eb98dcbe3 |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79d31a9e8819096e6a3040b1852a9 |
completed | March 28, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79dcae54c8190b06e687236373f68 |
completed | March 28, 2026, 9:22 a.m. |
Created at: March 27, 2026, 2:43 p.m.