Triple
T17221597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kay Thorpe |
E417996
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Mills & Boon |
E1257215
|
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: Mills & Boon | Statement: [Kay Thorpe, associatedWith, Mills & Boon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mills & Boon Context triple: [Kay Thorpe, associatedWith, Mills & Boon]
-
A.
Mills & Boon
chosen
Mills & Boon is a British publishing house best known for its prolific output of popular romance novels.
-
B.
Harlequin Enterprises
Harlequin Enterprises is a major publisher best known for its mass-market romance novels and global reach in the popular fiction market.
-
C.
Avon Books
Avon Books is a major American paperback and romance fiction publisher that operates as an imprint of HarperCollins.
-
D.
Harlequin
Harlequin is a classic comic servant character from the Italian commedia dell’arte tradition, known for his colorful diamond-patterned costume, acrobatic antics, and mischievous, witty personality.
-
E.
Harlequin
Harlequin is a major publishing imprint best known for its extensive catalog of romance novels and commercial fiction.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dde78f881908b03105fa0298ae2 |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170ed74688190b15ef6d7e0cebe86 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:38 a.m.