Triple
T8474204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Crispi |
E200349
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Ribera |
E146989
|
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: Ribera | Statement: [Francesco Crispi, placeOfBirth, Ribera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ribera Context triple: [Francesco Crispi, placeOfBirth, Ribera]
-
A.
Ribera
chosen
Ribera was a prominent 17th-century Spanish Baroque painter, known for his dramatic use of light and shadow and intense religious and genre scenes.
-
B.
La Ribera
La Ribera is a historic neighborhood in Barcelona known for its medieval streets, vibrant cultural scene, and notable attractions such as the Picasso Museum.
-
C.
Ribera d’Ebre
Ribera d’Ebre is a comarca (county) in Catalonia, Spain, known for its strategic position along the Ebro River and as a key setting of the Spanish Civil War’s Battle of the Ebro.
-
D.
Alberche River
The Alberche River is a significant river in central Spain that flows through the provinces of Ávila, Madrid, and Toledo before joining the Tagus.
-
E.
Ribeira
Ribeira is a historic riverside district in Porto, Portugal, known for its narrow medieval streets, colorful buildings, and vibrant waterfront atmosphere along the Douro River.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f7328481909ad19bcf8d182022 |
completed | March 31, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4de1fae48190a1149f639faca147 |
completed | April 2, 2026, 11:07 a.m. |
Created at: March 30, 2026, 6:11 p.m.