Triple
T7356750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Psych |
E169644
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Kirsten Nelson
Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
|
E691597
|
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: Kirsten Nelson | Statement: [Psych, starring, Kirsten Nelson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirsten Nelson Context triple: [Psych, starring, Kirsten Nelson]
-
A.
Kirsten Elms
Kirsten Elms is a screenwriter best known for co-writing the horror film "Texas Chainsaw 3D."
-
B.
Kirsten Corley
Kirsten Corley is an American former model and real estate agent best known as the wife of hip-hop artist Chance the Rapper.
-
C.
Kirsten Smith
Kirsten Smith is an American screenwriter and producer best known for co-writing popular teen and romantic comedies such as "Legally Blonde," "10 Things I Hate About You," and "Ella Enchanted."
-
D.
Kirsten Downey
Kirsten Downey is an American journalist and biographer known for her work at The Washington Post and for writing acclaimed historical biographies such as "The Woman Behind the New Deal."
-
E.
Joanna Kerns
Joanna Kerns is an American actress best known for playing the mother, Maggie Seaver, on the 1980s television sitcom "Growing Pains."
- 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: Kirsten Nelson Triple: [Psych, starring, Kirsten Nelson]
Generated description
Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kirsten Nelson Target entity description: Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
-
A.
Kirsten Elms
Kirsten Elms is a screenwriter best known for co-writing the horror film "Texas Chainsaw 3D."
-
B.
Kirsten Corley
Kirsten Corley is an American former model and real estate agent best known as the wife of hip-hop artist Chance the Rapper.
-
C.
Kirsten Smith
Kirsten Smith is an American screenwriter and producer best known for co-writing popular teen and romantic comedies such as "Legally Blonde," "10 Things I Hate About You," and "Ella Enchanted."
-
D.
Kirsten Downey
Kirsten Downey is an American journalist and biographer known for her work at The Washington Post and for writing acclaimed historical biographies such as "The Woman Behind the New Deal."
-
E.
Joanna Kerns
Joanna Kerns is an American actress best known for playing the mother, Maggie Seaver, on the 1980s television sitcom "Growing Pains."
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f13a62e48190a2d1781a630aa9f0 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9953aff988190a3224050e5706589 |
completed | March 29, 2026, 9:10 p.m. |
| NEDg | Description generation | batch_69c996242f18819094d043f3e7f6be53 |
completed | March 29, 2026, 9:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9967b4b44819096a577e75ecc3975 |
completed | March 29, 2026, 9:15 p.m. |
Created at: March 27, 2026, 3:06 p.m.