Triple
T20212408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Humble |
E493520
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kate Humble |
—
|
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 Humble | Statement: [Kate Humble, name, Kate Humble]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Humble Context triple: [Kate Humble, name, Kate Humble]
-
A.
Kate Humble
chosen
Kate Humble is a British television presenter and author best known for hosting wildlife and science programmes on the BBC.
-
B.
Elizabeth Dauncey
Elizabeth Dauncey was the wife of American screenwriter Waldemar Young, known primarily through her marriage to this prominent Hollywood figure.
-
C.
Elizabeth Dauncey
Elizabeth Dauncey was the daughter of Sir Thomas More and a learned Tudor gentlewoman known for her humanist education and correspondence.
-
D.
Verity Faulks
Verity Faulks is the wife of British novelist Sebastian Faulks, known for maintaining a private life largely out of the public eye despite her husband's literary prominence.
-
E.
Elizabeth Kempton
Elizabeth Kempton is best known as the wife of American actor and dancer Russ Tamblyn.
- 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.