Triple
T20453022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do Revenge |
E501702
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Sophie Turner |
—
|
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: Sophie Turner | Statement: [Do Revenge, castMember, Sophie Turner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sophie Turner Context triple: [Do Revenge, castMember, Sophie Turner]
-
A.
Sophie Turner
chosen
Sophie Turner is an English actress best known for her role as Sansa Stark in the television series "Game of Thrones."
-
B.
Emilia Clarke
Emilia Clarke is an English actress best known for her role as Daenerys Targaryen in the television series "Game of Thrones."
-
C.
Natalie Dormer
Natalie Dormer is an English actress best known for her role as Margaery Tyrell in the television series "Game of Thrones" and for notable performances in projects such as "The Tudors" and "The Hunger Games" films.
-
D.
Saskia Reeves
Saskia Reeves is a British actress known for her work in film, television, and theatre, including roles in series such as "Luther" and numerous acclaimed stage productions.
-
E.
Nathalie Emmanuel
Nathalie Emmanuel is a British actress best known for her roles as Missandei in "Game of Thrones" and Ramsey in the "Fast & Furious" film franchise.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68d039af08190827bf765b50515a8 |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.