Triple
T18416162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caitlin |
E441895
|
entity |
| Predicate | hasParent |
P120
|
FINISHED |
| Object | Samantha Caine |
—
|
NE NERFINISHED |
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: Samantha Caine | Statement: [Caitlin, hasParent, Samantha Caine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samantha Caine Context triple: [Caitlin, hasParent, Samantha Caine]
-
A.
Samantha Caine
chosen
Samantha Caine is the amnesiac suburban schoolteacher who gradually uncovers her past as a lethal government assassin in the action thriller "The Long Kiss Goodnight."
-
B.
Samantha Logan
Samantha Logan is an American actress best known for her leading role as Olivia Baker in the television drama series "All American."
-
C.
Samantha Taggart
Samantha Taggart is a strong-willed, street-smart emergency room nurse on the television series "ER," known for her resilience and complex personal relationships.
-
D.
Samantha Lorraine
Samantha Lorraine is an American actress best known for her role in the Netflix coming-of-age comedy film "You Are So Not Invited to My Bat Mitzvah."
-
E.
Samara Morgan
Samara Morgan is the vengeful ghostly girl from the horror film "The Ring," known for her cursed videotape and terrifying emergence from television screens.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a284b608190b77c360a72aceb7a |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 10:47 a.m.