Triple
T2551935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances Burney |
E56645
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cecilia |
E135814
|
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: Cecilia | Statement: [Frances Burney, notableWork, Cecilia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cecilia Context triple: [Frances Burney, notableWork, Cecilia]
-
A.
Cecilia
chosen
Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
-
B.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
C.
Lucia
Lucia is a feminine given name of Latin origin, commonly associated with light and used in various European cultures.
-
D.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
E.
Valeria
Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd30a91348190aea0dbd1efb6f8cc |
completed | March 7, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d14a58c819094250ee393f95a37 |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:48 p.m.