Triple
T21538311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moro River |
E531410
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Lanciano |
—
|
NE NERFINISHED |
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: Lanciano | Statement: [Moro River, near, Lanciano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lanciano Context triple: [Moro River, near, Lanciano]
-
A.
Lanciano
chosen
Lanciano is a historic town in Italy’s Abruzzo region, known for its medieval architecture and as the site of a famous Eucharistic miracle.
-
B.
Osimo
Osimo is a historic town in Italy’s Marche region, known for its medieval architecture and its role as the signing site of the Treaty of Osimo between Italy and Yugoslavia.
-
C.
Aversa
Aversa is a historic city in southern Italy’s Campania region, known for its medieval origins and proximity to Naples.
-
D.
Pioltello
Pioltello is a municipality in the Metropolitan City of Milan in Lombardy, northern Italy, known as a residential and industrial suburb of Milan.
-
E.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0fdf448190b47ac7c28904f86b |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.