Triple

T34842919
Position Surface form Disambiguated ID Type / Status
Subject Dennis Lau & Ng Chun Man Architects & Engineers E1004388 entity
Predicate namedAfter P63 FINISHED
Object Ng Chun Man
Ng Chun Man is an architect and engineer after whom the Hong Kong-based firm Dennis Lau & Ng Chun Man Architects & Engineers is named.
E2117716 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: Ng Chun Man | Statement: [Dennis Lau & Ng Chun Man Architects & Engineers, namedAfter, Ng Chun Man]
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: Ng Chun Man
Triple: [Dennis Lau & Ng Chun Man Architects & Engineers, namedAfter, Ng Chun Man]
Generated description
Ng Chun Man is an architect and engineer after whom the Hong Kong-based firm Dennis Lau & Ng Chun Man Architects & Engineers is named.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7813183f08190937aa3c571e214b7 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786cc0d3c819098bc7ca6e5baa841 completed June 21, 2026, 6:38 a.m.
NEDg Description generation batch_6a3789c680f48190857af3d89addc40e completed June 21, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_6a378aae279481908b987c43ffd8c594 completed June 21, 2026, 6:54 a.m.
Created at: May 3, 2026, 4 p.m.