Triple
T15027406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arona |
E378251
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Verbania |
E178417
|
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: Verbania | Statement: [Arona, hasNearbyCity, Verbania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verbania Context triple: [Arona, hasNearbyCity, Verbania]
-
A.
Verbania
chosen
Verbania is a lakeside city in northern Italy, situated on the shores of Lake Maggiore near the Swiss border.
-
B.
Parbhani
Parbhani is a significant city in the Marathwada region of Maharashtra, India, known as an important commercial and educational center.
-
C.
Chiplun
Chiplun is a town in Maharashtra, India, situated along the Vashishti River and known as a commercial and transport hub in the Konkan region.
-
D.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
-
E.
Banavasi
Banavasi is an ancient town in Karnataka, India, historically significant as an early capital of the Kadamba dynasty and a major center of early Kannada culture and inscriptions.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7dfcb508190aec8cd667e27a8ea |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5b0bbf4819082e14715bfd6003d |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:58 a.m.