Triple

T36313271
Position Surface form Disambiguated ID Type / Status
Subject Warangal–Hanamkonda–Kazipet tri-city E894118 entity
Predicate hasRailwayStation P918 FINISHED
Object Kazipet railway station
Kazipet railway station is a major railway junction in Telangana, India, serving the Warangal–Hanamkonda–Kazipet urban region and connecting key routes in South and Central India.
E2180769 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: Kazipet railway station | Statement: [Warangal–Hanamkonda–Kazipet tri-city, hasRailwayStation, Kazipet railway station]
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: Kazipet railway station
Triple: [Warangal–Hanamkonda–Kazipet tri-city, hasRailwayStation, Kazipet railway station]
Generated description
Kazipet railway station is a major railway junction in Telangana, India, serving the Warangal–Hanamkonda–Kazipet urban region and connecting key routes in South and 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_69f76e4d1a788190a6ab6ccca28547a7 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba25a0988190b7c864452b64730d completed May 3, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a3186f008190bcbe76eaba55401a completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a62d93dc81908598bf8f660186a2 completed June 22, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_6a39a6cc38948190a9ff65bd669afa19 completed June 22, 2026, 9:19 p.m.
Created at: May 3, 2026, 4:09 p.m.