Triple

T29673881
Position Surface form Disambiguated ID Type / Status
Subject Tung Chung Bay E750748 entity
Predicate adjacentTo P224 FINISHED
Object Ma Wan Chung Village
Ma Wan Chung Village is a traditional fishing village on Lantau Island in Hong Kong, known for its stilt houses, coastal setting, and proximity to the Tung Chung new town.
E1879553 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: Ma Wan Chung Village | Statement: [Tung Chung Bay, adjacentTo, Ma Wan Chung Village]
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: Ma Wan Chung Village
Triple: [Tung Chung Bay, adjacentTo, Ma Wan Chung Village]
Generated description
Ma Wan Chung Village is a traditional fishing village on Lantau Island in Hong Kong, known for its stilt houses, coastal setting, and proximity to the Tung Chung new town.

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_69f0d624d7b08190ba237d226f78d0d9 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f6725ac2d48190b0e65018d8294f94 completed May 2, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267ec01e988190979c5f0c9a25a162 completed June 8, 2026, 8:35 a.m.
NEDg Description generation batch_6a2682b72dc881909ee96a24b8cd2427 completed June 8, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a2687c32e1c8190a9da1493708e831e completed June 8, 2026, 9:13 a.m.
Created at: April 28, 2026, 7:06 p.m.