Triple
T17876015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannah Waterman |
E446954
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Hannah Waterman |
—
|
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: Hannah Waterman | Statement: [Hannah Waterman, name, Hannah Waterman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannah Waterman Context triple: [Hannah Waterman, name, Hannah Waterman]
-
A.
Hannah Waterman
chosen
Hannah Waterman is an English actress best known for her role as Laura Beale in the BBC soap opera EastEnders.
-
B.
Hannah Richings
Hannah Richings is a British singer and performer best known as a member of the pop group S Club 8, formed as a spin-off from S Club 7 in the early 2000s.
-
C.
Madeleine Harris
Madeleine Harris is a British actress best known for playing Judy Brown in the family film "Paddington" and its sequel.
-
D.
Lily Houghton
Lily Houghton is a fictional, adventurous British botanist and explorer from the film "Jungle Cruise."
-
E.
Sophie Dahl
Sophie Dahl is an English author and former fashion model, known for her novels and cookbooks as well as being the granddaughter of writer Roald Dahl.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa614b48190bdc9e905e9e6d5e0 |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 10:18 a.m.