Triple
T23025849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharine Sergeant Angell White |
E573309
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Katharine |
—
|
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: Katharine | Statement: [Katharine Sergeant Angell White, givenName, Katharine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katharine Context triple: [Katharine Sergeant Angell White, givenName, Katharine]
-
A.
Katharine
chosen
Katharine is a feminine given name of Greek origin, commonly used in various forms across Europe and the English-speaking world.
-
B.
Katherine
Katherine is a central character in the 2017 film "Albion," a fantasy adventure story involving a young girl transported to a magical realm.
-
C.
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.
-
D.
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.
-
E.
Katherine
Katherine is the mother of Thomasin.
- 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_69e245b821008190b0e09cb02092aae1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1847d7cb48190902169813c46a278 |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:52 p.m.