Triple

T35096924
Position Surface form Disambiguated ID Type / Status
Subject Jalandhar City railway station E1012889 entity
Predicate locatedOn P40 FINISHED
Object Jalandhar–Hoshiarpur line
The Jalandhar–Hoshiarpur line is a regional railway route in the Indian state of Punjab that connects the cities of Jalandhar and Hoshiarpur.
E2143402 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: Jalandhar–Hoshiarpur line | Statement: [Jalandhar City railway station, locatedOn, Jalandhar–Hoshiarpur 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: Jalandhar–Hoshiarpur line
Triple: [Jalandhar City railway station, locatedOn, Jalandhar–Hoshiarpur line]
Generated description
The Jalandhar–Hoshiarpur line is a regional railway route in the Indian state of Punjab that connects the cities of Jalandhar and Hoshiarpur.

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_69f76dd432ec8190969bc32acfc152b1 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78be523548190b4f3be5c9bb96d15 completed May 3, 2026, 5:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a17a34c8190915cf4f0778d6a7d completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384af0370c8190b49b96626cfb98c2 completed June 21, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a384b839a308190a63708ae678946da completed June 21, 2026, 8:37 p.m.
Created at: May 3, 2026, 4:01 p.m.