Triple
T19105272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen Bamber |
E467635
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Helen Bamber |
—
|
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: Helen Bamber | Statement: [Helen Bamber, name, Helen Bamber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Bamber Context triple: [Helen Bamber, name, Helen Bamber]
-
A.
Helen Bamber
chosen
Helen Bamber was a British psychotherapist and human rights activist renowned for her pioneering work with survivors of torture and extreme human cruelty.
-
B.
Hayley Roberts
Hayley Roberts is a Welsh former shop assistant and model best known for being married to actor and singer David Hasselhoff.
-
C.
Helen Gibson
Helen Gibson was a pioneering American silent film actress and stunt performer, best known as one of early cinema’s first professional stuntwomen.
-
D.
Catherine Durkan
Catherine Durkan is a notable individual associated with the Durkan family name, recognized as a bearer of this surname.
-
E.
Kristin Scott Thomas
Kristin Scott Thomas is an acclaimed British actress known for her nuanced performances in films such as "The English Patient," "Four Weddings and a Funeral," and "The Horse Whisperer."
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3704c688190b84ef82da45d0862 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.