Triple
T23389162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ring Two |
E593964
|
entity |
| Predicate | antagonist |
P4675
|
FINISHED |
| Object | Samara Morgan |
—
|
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: Samara Morgan | Statement: [The Ring Two, antagonist, Samara Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samara Morgan Context triple: [The Ring Two, antagonist, Samara Morgan]
-
A.
Samara Morgan
chosen
Samara Morgan is the vengeful ghostly girl from the horror film "The Ring," known for her cursed videotape and terrifying emergence from television screens.
-
B.
Taylor Morgan
Taylor Morgan is a member of the hip-hop and trap production collective Internet Money, known for crafting and collaborating on contemporary rap and melodic trap music.
-
C.
Samantha Kincaid
Samantha Kincaid is a fictional Portland deputy district attorney and protagonist of a legal thriller series by Alafair Burke.
-
D.
Samantha Caine
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."
-
E.
Tanee McCall
Tanee McCall is an American actress and professional dancer known for her roles in film and television, including action and dance-focused projects.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49a7c14819082aab826715976c5 |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:35 p.m.