Triple
T3205087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diff'rent Strokes |
E67141
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Todd Bridges
Todd Bridges is an American actor best known for playing Willis Jackson on the sitcom "Diff'rent Strokes."
|
E335272
|
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: Todd Bridges | Statement: [Diff'rent Strokes, portrayedBy, Todd Bridges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Todd Bridges Context triple: [Diff'rent Strokes, portrayedBy, Todd Bridges]
-
A.
Jake Scott
Jake Scott is a British film and music video director known for his work with prominent rock bands and artists.
-
B.
Jake Scott
Jake Scott was an American NFL safety best known for his standout play with the Miami Dolphins in the early 1970s, including their perfect season.
-
C.
Christian Broun
Christian Broun was a Scottish noblewoman best known as the mother of James Broun-Ramsay, 1st Marquess of Dalhousie, who served as Governor-General of India in the mid-19th century.
-
D.
Tom Love
Tom Love is an American computer scientist and software engineer best known as a co-creator of the Objective-C programming language.
-
E.
Tom Cross
Tom Cross is an Academy Award–winning American film editor known for his work on acclaimed movies such as "Whiplash" and "La La Land."
- 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: Todd Bridges Triple: [Diff'rent Strokes, portrayedBy, Todd Bridges]
Generated description
Todd Bridges is an American actor best known for playing Willis Jackson on the sitcom "Diff'rent Strokes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Todd Bridges Target entity description: Todd Bridges is an American actor best known for playing Willis Jackson on the sitcom "Diff'rent Strokes."
-
A.
Jake Scott
Jake Scott was an American NFL safety best known for his standout play with the Miami Dolphins in the early 1970s, including their perfect season.
-
B.
Jake Scott
Jake Scott is a British film and music video director known for his work with prominent rock bands and artists.
-
C.
Christian Broun
Christian Broun was a Scottish noblewoman best known as the mother of James Broun-Ramsay, 1st Marquess of Dalhousie, who served as Governor-General of India in the mid-19th century.
-
D.
Tom Love
Tom Love is an American computer scientist and software engineer best known as a co-creator of the Objective-C programming language.
-
E.
Tom Cross
Tom Cross is an Academy Award–winning American film editor known for his work on acclaimed movies such as "Whiplash" and "La La Land."
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa559848819082d1e61f586278dd |
completed | March 8, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bcbb0e88190b4413c4ba3de0eeb |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24ca05434819080ee515b1e7bdcb4 |
completed | March 12, 2026, 5:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b24d19250c81908a9c3ac95b83a473 |
completed | March 12, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:07 p.m.