Triple

T33651031
Position Surface form Disambiguated ID Type / Status
Subject Supreme Court Road E862097 entity
Predicate near P350 FINISHED
Object Central Government Complex (Tamar)
Central Government Complex (Tamar) is a major government headquarters development in Hong Kong’s Tamar area, housing key administrative offices including the Central Government Offices and the Chief Executive’s Office.
E2061182 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: Central Government Complex (Tamar) | Statement: [Supreme Court Road, near, Central Government Complex (Tamar)]
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: Central Government Complex (Tamar)
Triple: [Supreme Court Road, near, Central Government Complex (Tamar)]
Generated description
Central Government Complex (Tamar) is a major government headquarters development in Hong Kong’s Tamar area, housing key administrative offices including the Central Government Offices and the Chief Executive’s Office.

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_69f349840ba881908e3bfce536aeb92b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f9c222388190832312a168068257 completed May 3, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36271f98708190ae07b4042ad5c8a1 completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a36284edf948190bc8a444f2ab1ba14 completed June 20, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_6a3628e7bbfc81909a7cd7e8658c8e4d completed June 20, 2026, 5:45 a.m.
Created at: May 1, 2026, 1:42 a.m.