Triple
T13082641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annia Aurelia Fadilla |
E310248
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Annia |
E755695
|
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: Annia | Statement: [Annia Aurelia Fadilla, givenName, Annia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annia Context triple: [Annia Aurelia Fadilla, givenName, Annia]
-
A.
Annia
chosen
Annia was a Roman noblewoman of the late Republic, best known as the wife of the powerful consul and populist leader Lucius Cornelius Cinna.
-
B.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
C.
Aelia
Aelia was a Roman noblewoman best known as an early wife of the powerful Roman general and dictator Lucius Cornelius Sulla.
-
D.
Almirena
Almirena is a central soprano role in George Frideric Handel’s opera "Rinaldo," portrayed as the virtuous and beloved daughter of the Christian leader Goffredo.
-
E.
Arnissa
Arnissa is a small town in northern Greece situated close to Lake Vegoritida, known for its scenic lakeside setting and surrounding natural landscape.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9811add9881908a92186dab5b6d48 |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e272629c8190926dbc9df447b6c4 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9:01 p.m.