Triple

T32716607
Position Surface form Disambiguated ID Type / Status
Subject First World Hotel E836536 entity
Predicate near P350 FINISHED
Object Genting Skyway cable car
The Genting Skyway cable car is an aerial gondola lift in Genting Highlands, Malaysia, that transports visitors between the foothills and the mountaintop resort complex.
E2018858 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: Genting Skyway cable car | Statement: [First World Hotel, near, Genting Skyway cable car]
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: Genting Skyway cable car
Triple: [First World Hotel, near, Genting Skyway cable car]
Generated description
The Genting Skyway cable car is an aerial gondola lift in Genting Highlands, Malaysia, that transports visitors between the foothills and the mountaintop resort complex.

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_69f34935455881909088975d79460418 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c88759ac81909146f11012ed7ee5 completed May 3, 2026, 4:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349ed0f15c81909984a6c84aaed9b9 completed June 19, 2026, 1:43 a.m.
NEDg Description generation batch_6a349ff71e708190b399c8fd17f99cb3 completed June 19, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34a0da80488190af33f45d0933771c completed June 19, 2026, 1:52 a.m.
Created at: May 1, 2026, 1:11 a.m.