Triple
T10945338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharine Pember |
E258580
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Katharine |
E62170
|
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: Katharine | Statement: [Katharine Pember, givenName, Katharine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katharine Context triple: [Katharine Pember, givenName, Katharine]
-
A.
Katherine
Katherine is the central protagonist of the story "The Well," around whom the narrative’s main events and conflicts revolve.
-
B.
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.
-
C.
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.
-
D.
Katherine
Katherine is the daughter of Evelyn Mulwray in the 1974 film noir "Chinatown," whose parentage is central to the movie's mystery and emotional impact.
-
E.
Kathryn
chosen
Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770e9a89081908979efd1d9e6af66 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d733f7d88190b45df5c155ff5a46 |
completed | April 18, 2026, 12:58 a.m. |
Created at: April 8, 2026, 9:23 p.m.