Triple
T2768578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katya |
E61396
|
entity |
| Predicate | isFormOf |
P15288
|
FINISHED |
| Object | Catherine |
E8723
|
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: Catherine | Statement: [Katya, isFormOf, Catherine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catherine Context triple: [Katya, isFormOf, Catherine]
-
A.
Catherine
chosen
Catherine is a feminine given name of Greek origin, derived from Aikaterine and widely used in various forms across many cultures.
-
B.
Catherine Hyde
Catherine Hyde, later Catherine Douglas, Duchess of Queensberry, was an 18th-century British noblewoman and socialite known for her influential role in London high society.
-
C.
Louisa
Louisa is the middle name of Katharine Louisa Stanley, a 19th-century English writer and member of the prominent Stanley family.
-
D.
Louisa
Louisa is a fictional character from Jean Toomer’s modernist work "Cane," representing themes of love, memory, and the complexities of African American life in the early 20th-century South.
-
E.
Isabel
Isabel is a feminine given name of Spanish origin, widely used in Spanish- and Portuguese-speaking countries and borne by numerous notable historical and contemporary figures.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd6785d88190b99f99889463a962 |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6496dc88190b316d5b36bc5df67 |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:57 p.m.