Triple
T13339364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catania Centrale railway station |
E317782
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Agrigento |
E55843
|
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: Agrigento | Statement: [Catania Centrale railway station, connectsTo, Agrigento]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agrigento Context triple: [Catania Centrale railway station, connectsTo, Agrigento]
-
A.
Akragas
chosen
Akragas was an important ancient Greek city on the southern coast of Sicily, renowned for its wealth, powerful status, and monumental temples.
-
B.
Gela
Gela is an ancient Greek colonial city on the southern coast of Sicily that was a significant center of Magna Graecia.
-
C.
Gela
Gela is a river in southern Sicily, Italy, that flows into the Mediterranean Sea near the city of Gela.
-
D.
Gela
Gela is a mountain village in the Rhodope Mountains of southern Bulgaria, known for its scenic landscapes and traditional Bulgarian culture.
-
E.
Gela
Gela is an Oceanic language spoken primarily in the Solomon Islands, particularly on Nggela (Florida) Islands in Central Province.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d01bf8481908cd3a99e5557b972 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19226eb881908f76134a04e72548 |
completed | May 7, 2026, 10:58 p.m. |
Created at: April 9, 2026, 9:31 p.m.