Triple
T19815155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH 48 |
E476040
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Davanagere |
—
|
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: Davanagere | Statement: [NH 48, connectsCity, Davanagere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Davanagere Context triple: [NH 48, connectsCity, Davanagere]
-
A.
Shivamogga
Shivamogga is a city in the Malnad region of Karnataka, India, known for its scenic landscapes, proximity to waterfalls like Jog Falls, and role as a regional commercial and educational hub.
-
B.
Sullia
Sullia is a town in the Dakshina Kannada district of Karnataka, India, known as a local commercial and educational center in the region.
-
C.
Davangere
chosen
Davangere is a major city in central Karnataka, India, known for its textile industry, educational institutions, and distinctive local cuisine such as Davangere benne dosa.
-
D.
Gadag
Gadag is a historic town in Karnataka, India, renowned for its richly carved medieval temples and monuments from the Western Chalukya architectural tradition.
-
E.
Madikeri
Madikeri is a scenic hill town in Karnataka’s Coorg region, known for its cool climate, coffee plantations, and lush Western Ghats landscapes.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f861248190a633dd8d227d9697 |
completed | April 20, 2026, 4:31 p.m. |
Created at: April 10, 2026, 1:50 p.m.