Triple

T30113992
Position Surface form Disambiguated ID Type / Status
Subject Durg Junction E765361 entity
Predicate railwayLine P848 FINISHED
Object Raipur–Durg section
The Raipur–Durg section is a key railway corridor in the Indian state of Chhattisgarh that connects the cities of Raipur and Durg and forms part of an important route for passenger and freight traffic in central India.
E1901788 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: Raipur–Durg section | Statement: [Durg Junction, railwayLine, Raipur–Durg section]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Raipur–Durg section
Triple: [Durg Junction, railwayLine, Raipur–Durg section]
Generated description
The Raipur–Durg section is a key railway corridor in the Indian state of Chhattisgarh that connects the cities of Raipur and Durg and forms part of an important route for passenger and freight traffic in central India.

Provenance (5 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_69f22475ad7c8190be7f9541044a0bbb completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67dc294488190af7314b78253404e completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274ca889288190b5c2980f09e41510 completed June 8, 2026, 11:13 p.m.
NEDg Description generation batch_6a274e7e3d648190a4104865797e9c3f completed June 8, 2026, 11:21 p.m.
NED2 Entity disambiguation (via description) batch_6a274f4260908190b9c1d27aff447285 completed June 8, 2026, 11:24 p.m.
Created at: April 29, 2026, 7:11 p.m.