Triple
T5135898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patricia Kaas |
E115818
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Patricia Kaas |
E115818
|
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: Patricia Kaas | Statement: [Patricia Kaas, name, Patricia Kaas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patricia Kaas Context triple: [Patricia Kaas, name, Patricia Kaas]
-
A.
Patricia Kaas
chosen
Patricia Kaas is a French singer and actress known for her distinctive husky voice and modern take on classic chanson, blending pop, jazz, and cabaret influences.
-
B.
June Duprez
June Duprez was a British film actress best known for her roles in 1940s dramas and adventure films, including the classic "The Thief of Bagdad."
-
C.
Mireille Mathieu
Mireille Mathieu is a French chanteuse renowned for her powerful voice, classic chanson repertoire, and international success since the 1960s.
-
D.
Mary Calvi
Mary Calvi is an American television journalist and news anchor, best known for her work with WCBS-TV in New York City.
-
E.
Nelly Roussel
Nelly Roussel was a pioneering French feminist, neo-Malthusian activist, and orator known for her advocacy of birth control, women’s rights, and social reform in the early 20th century.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd785069108190bf9cfdc7d962d43f |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4d04b3c8190bfac5986e1bb89a5 |
completed | March 21, 2026, 4:18 p.m. |
Created at: March 20, 2026, 1:43 p.m.