Triple

T30225386
Position Surface form Disambiguated ID Type / Status
Subject Seraj Valley E768463 entity
Predicate hasAttraction P105 FINISHED
Object Raghupur Fort trek
Raghupur Fort trek is a scenic hiking route in Himachal Pradesh’s Seraj Valley, known for its lush meadows, panoramic Himalayan views, and the ruins of an ancient hilltop fort.
E1905620 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: Raghupur Fort trek | Statement: [Seraj Valley, hasAttraction, Raghupur Fort trek]
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: Raghupur Fort trek
Triple: [Seraj Valley, hasAttraction, Raghupur Fort trek]
Generated description
Raghupur Fort trek is a scenic hiking route in Himachal Pradesh’s Seraj Valley, known for its lush meadows, panoramic Himalayan views, and the ruins of an ancient hilltop fort.

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_69f2248108208190be60bf1af343ce70 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68021a1548190a3b341eab3fa6bbd completed May 2, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276440be9081909a80cd3699d7a613 completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2764f2c6588190b88039903b3d891c completed June 9, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a27661767f081909e0291186c5d6778 completed June 9, 2026, 1:02 a.m.
Created at: April 29, 2026, 7:35 p.m.