Triple
T12343877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Udaipur City railway station |
E294297
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Mysuru |
E80753
|
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: Mysuru | Statement: [Udaipur City railway station, connectsTo, Mysuru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mysuru Context triple: [Udaipur City railway station, connectsTo, Mysuru]
-
A.
Mysuru
chosen
Mysuru is a historic city in the southern Indian state of Karnataka, renowned for its royal heritage, palaces, and cultural festivals such as Dasara.
-
B.
Madikeri
Madikeri is a scenic hill town in Karnataka’s Coorg region, known for its cool climate, coffee plantations, and lush Western Ghats landscapes.
-
C.
Davangere
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.
Sullia
Sullia is a town in the Dakshina Kannada district of Karnataka, India, known as a local commercial and educational center in the region.
-
E.
Mangalore
Mangalore is a major port city on the southwestern coast of India, known for its maritime trade, diverse culture, and role as a commercial hub of Karnataka.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f78a970819086beec3e4da8c49e |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6346dd09481908f4c80e89e2f4705 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:53 p.m.