Triple
T19277443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adrano |
E482092
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Catania |
—
|
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: Catania | Statement: [Adrano, nearbyCity, Catania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Catania Context triple: [Adrano, nearbyCity, Catania]
-
A.
Catania
chosen
Catania is a historic port city on the eastern coast of Sicily, Italy, known for its Baroque architecture and proximity to Mount Etna.
-
B.
Palermo
Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
-
C.
Palermo
Palermo is a municipality in the Huila Department of southern Colombia, known for its agricultural activities and proximity to the departmental capital, Neiva.
-
D.
Palermo
Palermo is an unincorporated community and census-designated place within Upper Township in Cape May County, New Jersey, known for its residential character and proximity to the Jersey Shore.
-
E.
Palermo
Palermo is a 90 nm, low-power, budget-oriented core used in AMD's Sempron line of processors.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbd5f34819086535f28fd880411 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:30 p.m.