Triple
T20254203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Knox (Lantana character) |
E498640
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Knox |
—
|
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: Knox | Statement: [John Knox (Lantana character), hasFamilyName, Knox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knox Context triple: [John Knox (Lantana character), hasFamilyName, Knox]
-
A.
Knox
chosen
Knox is a surname most famously associated with Henry Knox, a key American Revolutionary War general and the first United States Secretary of War.
-
B.
Knox-Shaw
Knox-Shaw is a British surname most notably associated with astronomer Harold Knox-Shaw.
-
C.
Harrison
Harrison is a common English surname borne by numerous notable figures across politics, the arts, and sciences.
-
D.
Harrison
Harrison is a city in New Jersey’s Hudson County, known as a residential and industrial community within the New York metropolitan area.
-
E.
Harrison
Harrison is a small lakeside city in northern Idaho known for its scenic location on Lake Coeur d'Alene and outdoor recreation opportunities.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673aa42348190852ae8313f4494ca |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.