Triple

T36363097
Position Surface form Disambiguated ID Type / Status
Subject Zip World Titan E895546 entity
Predicate partOfBrand P6092 FINISHED
Object Zip World adventure parks
Zip World adventure parks is a UK-based adventure tourism company known for its high-adrenaline outdoor attractions such as giant zip lines, underground adventures, and unique aerial experiences.
E2180319 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: Zip World adventure parks | Statement: [Zip World Titan, partOfBrand, Zip World adventure parks]
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: Zip World adventure parks
Triple: [Zip World Titan, partOfBrand, Zip World adventure parks]
Generated description
Zip World adventure parks is a UK-based adventure tourism company known for its high-adrenaline outdoor attractions such as giant zip lines, underground adventures, and unique aerial experiences.

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_69f76e5044248190b390d8887dc03254 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bacb7a70819083e74d2cfa28cf36 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a331eeb4819093ec8915b0bb47ac completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a72b9a148190b83e1ecbadb0f8ab completed June 22, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a39a7dc5c708190b35914ed21dead24 completed June 22, 2026, 9:23 p.m.
Created at: May 3, 2026, 4:10 p.m.