Triple
T20406629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Katherine Manners |
E500483
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Katherine |
—
|
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: Katherine | Statement: [Lady Katherine Manners, givenName, Katherine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katherine Context triple: [Lady Katherine Manners, givenName, Katherine]
-
A.
Katherine
Katherine is the central protagonist of the story "The Well," around whom the narrative’s main events and conflicts revolve.
-
B.
Katherine
chosen
Katherine is a feminine given name of Greek origin, commonly associated with meanings related to purity.
-
C.
Katherine
Katherine is a central character in the 2017 film "Albion," a fantasy adventure story involving a young girl transported to a magical realm.
-
D.
Katherine
Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
-
E.
Katherine
Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67993dc7081908ebd54ec92e712ea |
completed | April 20, 2026, 7:08 p.m. |
Created at: April 16, 2026, 11:29 a.m.