Triple
T10799129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Duke |
E254790
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Brody Duke
Brody Duke was an American tobacco industrialist and member of the prominent Duke family that helped shape the tobacco industry in the late 19th century.
|
E886459
|
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: Brody Duke | Statement: [Washington Duke, child, Brody Duke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brody Duke Context triple: [Washington Duke, child, Brody Duke]
-
A.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
-
B.
Gage Creed
Gage Creed is a young boy whose tragic death and supernatural resurrection drive the central horror and emotional conflict in Stephen King’s novel "Pet Sematary."
-
C.
Brody Bruce
Brody Bruce is a comic book–obsessed slacker and central character from Kevin Smith’s film "Mallrats," known for his sarcastic wit and pop-culture rants.
-
D.
Caspian Vaughn
Caspian Vaughn is a son of German supermodel and actress Claudia Schiffer.
-
E.
Alec Hardison
Alec Hardison is a brilliant, pop-culture-savvy hacker and tech expert who handles all things digital and logistical for the Leverage crew.
- 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: Brody Duke Triple: [Washington Duke, child, Brody Duke]
Generated description
Brody Duke was an American tobacco industrialist and member of the prominent Duke family that helped shape the tobacco industry in the late 19th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brody Duke Target entity description: Brody Duke was an American tobacco industrialist and member of the prominent Duke family that helped shape the tobacco industry in the late 19th century.
-
A.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
-
B.
Gage Creed
Gage Creed is a young boy whose tragic death and supernatural resurrection drive the central horror and emotional conflict in Stephen King’s novel "Pet Sematary."
-
C.
Brody Bruce
Brody Bruce is a comic book–obsessed slacker and central character from Kevin Smith’s film "Mallrats," known for his sarcastic wit and pop-culture rants.
-
D.
Caspian Vaughn
Caspian Vaughn is a son of German supermodel and actress Claudia Schiffer.
-
E.
Alec Hardison
Alec Hardison is a brilliant, pop-culture-savvy hacker and tech expert who handles all things digital and logistical for the Leverage crew.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73334feb08190aae967eaa37659f7 |
completed | April 9, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de566352608190ab15e3a4b690c9a5 |
completed | April 14, 2026, 2:59 p.m. |
| NEDg | Description generation | batch_69de5eaf3cc08190935cb6ddf2020166 |
completed | April 14, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de63a902f4819089845bc6d7469c6b |
completed | April 14, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:17 p.m.