Triple

T34745866
Position Surface form Disambiguated ID Type / Status
Subject Lung Cheung Road E1001633 entity
Predicate hasJunctionWith P1018 FINISHED
Object Tseuk Luk Street
Tseuk Luk Street is a local street in Hong Kong’s Wong Tai Sin District, known for connecting residential and industrial areas near major routes like Lung Cheung Road.
E2126852 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: Tseuk Luk Street | Statement: [Lung Cheung Road, hasJunctionWith, Tseuk Luk Street]
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: Tseuk Luk Street
Triple: [Lung Cheung Road, hasJunctionWith, Tseuk Luk Street]
Generated description
Tseuk Luk Street is a local street in Hong Kong’s Wong Tai Sin District, known for connecting residential and industrial areas near major routes like Lung Cheung Road.

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_69f76db0367081909b57c50a7fb03025 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779d317f88190bf3491fa92b555f8 completed May 3, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d9341d048190b0f208e97fa0eba5 completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37da28a3bc8190b36abb1d36a5c930 completed June 21, 2026, 12:33 p.m.
NED2 Entity disambiguation (via description) batch_6a37db99ec64819084312c5bc5269fe3 completed June 21, 2026, 12:39 p.m.
Created at: May 3, 2026, 3:59 p.m.