Triple
T20212397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Oddie |
E493519
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Kate Hardie |
—
|
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: Kate Hardie | Statement: [Bill Oddie, hasChild, Kate Hardie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Hardie Context triple: [Bill Oddie, hasChild, Kate Hardie]
-
A.
Kate Hardie
chosen
Kate Hardie is a British actress and writer known for her work in independent films and television dramas.
-
B.
Helen McDougall
Helen McDougall, better known by her stage name Helen Mack, was an American actress who appeared in films, radio, and early television during the 1930s and 1940s.
-
C.
Amy Hargreaves
Amy Hargreaves is an American actress known for her work in film and television, including roles in projects like the thriller "Blue Ruin" and the series "Homeland" and "13 Reasons Why."
-
D.
Beth Dawes
Beth Dawes is a married suburban woman in the television series "Mad Men" who becomes romantically involved with advertising executive Pete Campbell.
-
E.
Laura Haddock
Laura Haddock is an English actress known for her roles in films like "Guardians of the Galaxy" and various British television series.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ed627f48190a8ba638b85977af3 |
completed | April 20, 2026, 6:22 p.m. |
Created at: April 11, 2026, 11:38 p.m.