Triple

T37115952
Position Surface form Disambiguated ID Type / Status
Subject Diva Junction E919116 entity
Predicate hasSuburbanConnectivity P68952 FINISHED
Object Vasai Road–Roha corridor
The Vasai Road–Roha corridor is a key railway route in Maharashtra that links the Western and Central Railway networks, facilitating both suburban and freight movement across the Mumbai metropolitan region and the Konkan line.
E2215525 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: Vasai Road–Roha corridor | Statement: [Diva Junction, hasSuburbanConnectivity, Vasai Road–Roha corridor]
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: Vasai Road–Roha corridor
Triple: [Diva Junction, hasSuburbanConnectivity, Vasai Road–Roha corridor]
Generated description
The Vasai Road–Roha corridor is a key railway route in Maharashtra that links the Western and Central Railway networks, facilitating both suburban and freight movement across the Mumbai metropolitan region and the Konkan line.

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_69f76e9c57148190ba789dd059645bb9 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb3014e074819090b905bf6e06bdb0 completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a402ba39b10819094198622901ef658 completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402c5380008190b33806706655f030 completed June 27, 2026, 8:02 p.m.
NED2 Entity disambiguation (via description) batch_6a402e678e10819081e8b6b5bf2f233d completed June 27, 2026, 8:11 p.m.
Created at: May 3, 2026, 4:15 p.m.