Triple
T7356983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Psych 2: Lassie Come Home |
E169649
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Kirsten Nelson |
E691597
|
NE FINISHED |
How this triple was built (2 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 2: Lassie Come Home, stars, Kirsten Nelson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kirsten Nelson Context triple: [Psych 2: Lassie Come Home, stars, Kirsten Nelson]
-
A.
Kirsten Nelson
chosen
Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
-
B.
Kirsten Elms
Kirsten Elms is a screenwriter best known for co-writing the horror film "Texas Chainsaw 3D."
-
C.
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.
-
D.
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."
-
E.
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."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c9a53a44e48190bddf0f4faec136e7 |
completed | March 29, 2026, 10:18 p.m. |
Created at: March 27, 2026, 3:06 p.m.