Triple
T20353781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katni–Bilaspur line |
E496087
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Bilaspur, Chhattisgarh |
—
|
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: Bilaspur, Chhattisgarh | Statement: [Katni–Bilaspur line, connectsCity, Bilaspur, Chhattisgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bilaspur, Chhattisgarh Context triple: [Katni–Bilaspur line, connectsCity, Bilaspur, Chhattisgarh]
-
A.
Bilaspur
Bilaspur is a town in the Yamunanagar district of Haryana, India, known as a local commercial and administrative center for surrounding rural areas.
-
B.
Bilaspur
Bilaspur is a town in the Rampur district of Uttar Pradesh, India, known as a local commercial and administrative center for surrounding rural areas.
-
C.
Bilaspur
chosen
Bilaspur is a major city in the Indian state of Chhattisgarh, known as an important administrative, commercial, and judicial center.
-
D.
Bhopalgarh
Bhopalgarh is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the region.
-
E.
Jagdalpur
Jagdalpur is a city in the Bastar district of Chhattisgarh, India, known for its tribal culture, dense forests, and proximity to major waterfalls and national parks.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67851c7088190ba960a33c6dfa824 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.