Triple

T27536550
Position Surface form Disambiguated ID Type / Status
Subject Jonha Falls E695112 entity
Predicate railwayLine P848 FINISHED
Object Ranchi–Hatia–Bokaro–Dhanbad line
The Ranchi–Hatia–Bokaro–Dhanbad line is a key railway route in the Indian state of Jharkhand that connects major industrial and mining hubs, facilitating both passenger and freight transport.
 E1865437 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: Ranchi–Hatia–Bokaro–Dhanbad line | Statement: [Jonha Falls, railwayLine, Ranchi–Hatia–Bokaro–Dhanbad 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: Ranchi–Hatia–Bokaro–Dhanbad line
Triple: [Jonha Falls, railwayLine, Ranchi–Hatia–Bokaro–Dhanbad line]
Generated description
The Ranchi–Hatia–Bokaro–Dhanbad line is a key railway route in the Indian state of Jharkhand that connects major industrial and mining hubs, facilitating both passenger and freight transport.

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_69ef538608b081908b9f659bb09d5e0f completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f5a55ac8190877437ec33640bf0 completed May 2, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25c0c51b98819082e8f4333b51aabd completed June 7, 2026, 7:04 p.m.
NEDg Description generation batch_6a25c505c1e0819087cefd1331d571c1 completed June 7, 2026, 7:22 p.m.
NED2 Entity disambiguation (via description) batch_6a25cfde71e081909bd5db09781d4dbe completed June 7, 2026, 8:09 p.m.
Created at: April 27, 2026, 1:29 p.m.