Triple
T7862631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Fiennes |
E182535
|
entity |
| Predicate | notableRelative |
P367
|
FINISHED |
| Object | Sophie Fiennes |
E182536
|
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: Sophie Fiennes | Statement: [Mark Fiennes, notableRelative, Sophie Fiennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sophie Fiennes Context triple: [Mark Fiennes, notableRelative, Sophie Fiennes]
-
A.
Sophie Fiennes
chosen
Sophie Fiennes is a British film director and producer known for her innovative documentaries and collaborations with artists and philosophers.
-
B.
Martha Fiennes
Martha Fiennes is a British film director, writer, and producer best known for her visually distinctive adaptation of "Onegin."
-
C.
Emily Watson
Emily Watson is an acclaimed English actress known for her powerful performances in films such as "Breaking the Waves," "Hilary and Jackie," and "Punch-Drunk Love."
-
D.
Rebecca Hall
Rebecca Hall is a British-American actress and filmmaker known for her nuanced performances in films such as "Vicky Cristina Barcelona," "The Town," and "Christine."
-
E.
Rachel Weisz
Rachel Weisz is an Academy Award–winning British actress known for her versatile performances in films such as "The Constant Gardener," "The Mummy," and "The Favourite."
- 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.