Triple
T16369607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hothouse Flower |
E397529
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Lucinda Riley |
E88093
|
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: Lucinda Riley | Statement: [Hothouse Flower, author, Lucinda Riley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucinda Riley Context triple: [Hothouse Flower, author, Lucinda Riley]
-
A.
Lucinda Riley
chosen
Lucinda Riley was a bestselling Irish author best known for her multi-volume historical fiction series "The Seven Sisters," which achieved international acclaim.
-
B.
Lucinda McCullough
Lucinda McCullough was the wife of renowned American bridge engineer Conde McCullough, associated with his personal and family life during his career in Oregon.
-
C.
Elizabeth Knapp
Elizabeth Knapp was the mother of Elizabeth Shaw Melville, who was the wife of American novelist Herman Melville.
-
D.
Francine Rivers
Francine Rivers is a bestselling American author known for her inspirational Christian fiction novels, particularly "Redeeming Love."
-
E.
Linda Howard
Linda Howard is a fictional protagonist featured in the film "Lost in America."
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff4021e88190ad093bab74cf82a4 |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007d9c8de4819093ae3901cf0c8805 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:08 a.m.