Triple

T27317846
Position Surface form Disambiguated ID Type / Status
Subject Kanpur Central E689397 entity
Predicate liesOnRailwayLine P848 FINISHED
Object Kanpur–Lucknow line
The Kanpur–Lucknow line is a major Indian Railways route in Uttar Pradesh that connects the important cities of Kanpur and Lucknow, serving as a key commuter and intercity corridor.
 E1787700 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: Kanpur–Lucknow line | Statement: [Kanpur Central, liesOnRailwayLine, Kanpur–Lucknow line]
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: Kanpur–Lucknow line
Triple: [Kanpur Central, liesOnRailwayLine, Kanpur–Lucknow line]
Generated description
The Kanpur–Lucknow line is a major Indian Railways route in Uttar Pradesh that connects the important cities of Kanpur and Lucknow, serving as a key commuter and intercity corridor.

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_69ef355c53a08190a8a92e355a7ce115 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627e7a7b481908ddd375e2f2f10c8 completed May 2, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e4339b8c8190a4a8898f14807e67 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4bc42e081909864bb2839e08143 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e551ec288190b818e25bf2e62f45 completed May 24, 2026, 11:47 a.m.
Created at: April 27, 2026, 11:31 a.m.