Triple
T19634150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karwar railway station |
E471344
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Madgaon |
—
|
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: Madgaon | Statement: [Karwar railway station, connectsTo, Madgaon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madgaon Context triple: [Karwar railway station, connectsTo, Madgaon]
-
A.
Madgaon
chosen
Madgaon is a major commercial and cultural city in the South Goa district of the Indian state of Goa.
-
B.
Alibag
Alibag is a coastal town in Maharashtra, India, known for its beaches, historic forts, and role as a popular weekend getaway from Mumbai.
-
C.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
D.
Dalgaon
Dalgaon is a town and administrative center located in the Darrang district of the northeastern Indian state of Assam.
-
E.
Ratnagiri
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64104ff2881908fec49b7fba5a2e6 |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.