Triple
T9870353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biferno River |
E239939
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Larino |
E345745
|
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: Larino | Statement: [Biferno River, flowsNear, Larino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larino Context triple: [Biferno River, flowsNear, Larino]
-
A.
Larino
chosen
Larino is a historic town in the Molise region of southern Italy, known for its Roman amphitheater, medieval architecture, and traditional festivals.
-
B.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
C.
Varela
Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
-
D.
Peñafiel
Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero region.
-
E.
Santena
Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d62628819094786a49b9bcd09b |
completed | April 2, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e468630c81908d5c72f70e2c6fe4 |
completed | April 5, 2026, 4:26 a.m. |
Created at: March 30, 2026, 8:36 p.m.