Triple

T25343282
Position Surface form Disambiguated ID Type / Status
Subject Gunung Buda E635473 entity
Predicate partOf P40 FINISHED
Object Gunung Buda National Park
Gunung Buda National Park is a protected area in northern Sarawak, Malaysian Borneo, known for its limestone karst landscapes, extensive cave systems, and rich tropical rainforest biodiversity.
E1687337 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: Gunung Buda National Park | Statement: [Gunung Buda, partOf, Gunung Buda National Park]
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: Gunung Buda National Park
Triple: [Gunung Buda, partOf, Gunung Buda National Park]
Generated description
Gunung Buda National Park is a protected area in northern Sarawak, Malaysian Borneo, known for its limestone karst landscapes, extensive cave systems, and rich tropical rainforest biodiversity.

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_69e75a99bd6481909476115b35b9a8e4 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f498b936f08190b750199798e9effc completed May 1, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b72b8c8481908c9b8bd70f619b7b completed May 22, 2026, 8:06 p.m.
NEDg Description generation batch_6a10b7fa6d60819097ff930865af4032 completed May 22, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9606818819094491a74c5922378 completed May 22, 2026, 8:15 p.m.
Created at: April 21, 2026, 1:32 p.m.