Triple
T3269055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carine |
E68597
|
entity |
| Predicate | derivedFrom |
P909
|
FINISHED |
| Object | Katherine |
E89155
|
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: Katherine | Statement: [Carine, derivedFrom, Katherine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katherine Context triple: [Carine, derivedFrom, Katherine]
-
A.
Katherine
chosen
Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
-
B.
Kathryn
Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
-
C.
Katherine Carey
Katherine Carey was an English noblewoman of the late 16th century, a member of the influential Carey family closely connected to the Tudor court.
-
D.
Eleanor
Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
-
E.
Eleanor
Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
- 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafd0eddc8190834a64f6b8e8e9f9 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e83e11f081909d64287c0902124a |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:09 p.m.