Triple
T2696431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giacomo Leopardi |
E58520
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | A Silvia |
E169305
|
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: A Silvia | Statement: [Giacomo Leopardi, notableWork, A Silvia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A Silvia Context triple: [Giacomo Leopardi, notableWork, A Silvia]
-
A.
Silvia
chosen
Silvia is a feminine given name used in various languages, often associated with the Latin word for "forest" or "woods."
-
B.
Cecilia
Cecilia is a feminine given name of Latin origin, traditionally associated with Saint Cecilia, the patron saint of music.
-
C.
The Lady
The Lady is the mysterious, sharpshooting female gunslinger who enters a deadly quick-draw tournament to confront her past in the Western film "The Quick and the Dead."
-
D.
Quarrel
Quarrel is a supporting character in the James Bond film series, portrayed as a loyal Cayman Islander ally who assists Bond in his Caribbean missions.
-
E.
Maud
Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda3112108190a5e49c13368cf83f |
completed | March 7, 2026, 7:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf6aa78c8190b57be36042008361 |
completed | March 10, 2026, 5:43 a.m. |
Created at: March 6, 2026, 9:55 p.m.