Triple
T7862670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Fiennes |
E182536
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fiennes |
E175427
|
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: Fiennes | Statement: [Sophie Fiennes, familyName, Fiennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fiennes Context triple: [Sophie Fiennes, familyName, Fiennes]
-
A.
Fiennes
chosen
Fiennes is an English surname most prominently associated with a family of notable actors and explorers, including Ralph and Joseph Fiennes.
-
B.
Jacob Fiennes
Jacob Fiennes is a member of the Fiennes family, known as a relative of English actor Joseph Fiennes.
-
C.
William Fiennes
William Fiennes is an English writer and memoirist best known for his acclaimed books "The Snow Geese" and "The Music Room."
-
D.
Magnus Fiennes
Magnus Fiennes is a British composer, record producer, and songwriter known for his work in film, television, and pop music.
-
E.
Ralph Fiennes
Ralph Fiennes is an acclaimed English actor and filmmaker known for his intense, nuanced performances in films such as Schindler's List, the Harry Potter series, and The Grand Budapest Hotel.
- 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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb36be5f408190b82a097b0825c57a |
completed | March 31, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbdbcede08190af889a5228de01f5 |
completed | April 1, 2026, 6:39 a.m. |
Created at: March 30, 2026, 4:53 p.m.