Triple

T31929026
Position Surface form Disambiguated ID Type / Status
Subject Bhusawal railway division E815191 entity
Predicate hasRoute P4374 FINISHED
Object Manmad–Jalgaon section
The Manmad–Jalgaon section is a key railway line in Maharashtra, India, forming part of the main route connecting central and northern India with Mumbai.
 E1521221 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: Manmad–Jalgaon section | Statement: [Bhusawal railway division, hasRoute, Manmad–Jalgaon 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: Manmad–Jalgaon section
Triple: [Bhusawal railway division, hasRoute, Manmad–Jalgaon section]
Generated description
The Manmad–Jalgaon section is a key railway line in Maharashtra, India, forming part of the main route connecting central and northern India with Mumbai.

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_69f348f1df848190851bbfb988da3414 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b22e7f6c8190a6168995dc94c636 completed May 3, 2026, 2:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46b31cc88190acee1894654d391a completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f4831a32c8190ad20aa36509c985f completed June 15, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_6a2f48982324819085c67bfe1168b66d completed June 15, 2026, 12:34 a.m.
Created at: May 1, 2026, 12:04 a.m.