Triple

T26997148
Position Surface form Disambiguated ID Type / Status
Subject High Courts of Nepal E680005 entity
Predicate hasComponent P35 FINISHED
Object Pokhara High Court
Pokhara High Court is a provincial-level appellate court in Nepal’s judiciary that hears civil and criminal cases from its jurisdiction in and around Pokhara.
E1755014 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: Pokhara High Court | Statement: [High Courts of Nepal, hasComponent, Pokhara High Court]
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: Pokhara High Court
Triple: [High Courts of Nepal, hasComponent, Pokhara High Court]
Generated description
Pokhara High Court is a provincial-level appellate court in Nepal’s judiciary that hears civil and criminal cases from its jurisdiction in and around Pokhara.

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_69eeeb52908c8190bd246244686aa455 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6219552e0819080e649ca35c52621 completed May 2, 2026, 4:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ab2121c8190a9d351ad0ed13317 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123ba9aea081909f20ff78ab91747e completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c4f67388190a885b5ce89f9baa6 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 6:55 a.m.