Triple
T2593460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunhill |
E58176
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object |
Davidoff
Davidoff is a premium lifestyle brand best known for its luxury cigars, tobacco products, and fragrances.
|
E280841
|
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: Davidoff | Statement: [Dunhill, competesWith, Davidoff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Davidoff Context triple: [Dunhill, competesWith, Davidoff]
-
A.
Dunhill
Dunhill is a premium cigarette brand known for its association with luxury and high-quality tobacco products.
-
B.
Benson & Hedges
Benson & Hedges is a long-established premium cigarette brand known for its association with luxury and high-quality tobacco products.
-
C.
Ballantine
Ballantine is the surname of the individual after whom the prestigious Stuart Ballantine Medal for scientific and engineering achievement is named.
-
D.
Hennessy
Hennessy is a surname most prominently associated with John L. Hennessy, a renowned computer scientist and former president of Stanford University.
-
E.
Marlboro
Marlboro is a leading global cigarette brand, widely recognized for its red-and-white packaging and long-running "Marlboro Man" advertising campaign.
- 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: Davidoff Triple: [Dunhill, competesWith, Davidoff]
Generated description
Davidoff is a premium lifestyle brand best known for its luxury cigars, tobacco products, and fragrances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Davidoff Target entity description: Davidoff is a premium lifestyle brand best known for its luxury cigars, tobacco products, and fragrances.
-
A.
Dunhill
Dunhill is a premium cigarette brand known for its association with luxury and high-quality tobacco products.
-
B.
Benson & Hedges
Benson & Hedges is a long-established premium cigarette brand known for its association with luxury and high-quality tobacco products.
-
C.
Ballantine
Ballantine is the surname of the individual after whom the prestigious Stuart Ballantine Medal for scientific and engineering achievement is named.
-
D.
Hennessy
Hennessy is a surname most prominently associated with John L. Hennessy, a renowned computer scientist and former president of Stanford University.
-
E.
Marlboro
Marlboro is a leading global cigarette brand, widely recognized for its red-and-white packaging and long-running "Marlboro Man" advertising campaign.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd426e2d4819081a07920b4d2a1cc |
completed | March 7, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83bee4908190b5e446ddbf4e8889 |
completed | March 10, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69af8434f61c81909bffb3f06acb733b |
completed | March 10, 2026, 2:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af84b260b881909bbd3d2825f9dea7 |
completed | March 10, 2026, 2:40 a.m. |
Created at: March 6, 2026, 9:49 p.m.