Triple

T38358375
Position Surface form Disambiguated ID Type / Status
Subject Waterfall City mixed-use development E1046399 entity
Predicate hasComponent P35 FINISHED
Object Waterfall Corporate Campus
Waterfall Corporate Campus is a major business and office precinct within the Waterfall City mixed-use development in South Africa, hosting corporate headquarters and commercial facilities.
E2266542 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: Waterfall Corporate Campus | Statement: [Waterfall City mixed-use development, hasComponent, Waterfall Corporate Campus]
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: Waterfall Corporate Campus
Triple: [Waterfall City mixed-use development, hasComponent, Waterfall Corporate Campus]
Generated description
Waterfall Corporate Campus is a major business and office precinct within the Waterfall City mixed-use development in South Africa, hosting corporate headquarters and commercial facilities.

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_69f76e3a94fc81908edc175e8d259e80 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fcc73873fc8190b4b065db1e74a56d completed May 7, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7ff3d5081908ddaa9c83db92520 completed June 28, 2026, 11:02 p.m.
NEDg Description generation batch_6a41a963d4b08190aadb7c1c9f4bbea1 completed June 28, 2026, 11:08 p.m.
NED2 Entity disambiguation (via description) batch_6a41aa98dee081908e46b5d1e0bb13b1 completed June 28, 2026, 11:13 p.m.
Created at: May 3, 2026, 4:31 p.m.