Triple

T38340873
Position Surface form Disambiguated ID Type / Status
Subject Old Leather Factory site E1038097 entity
Predicate partOf P40 FINISHED
Object Peng Chau industrial area
Peng Chau industrial area is a former manufacturing district on Peng Chau Island in Hong Kong, known for its now-defunct factories and remnants of the island’s once-thriving industrial past.
E2265825 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: Peng Chau industrial area | Statement: [Old Leather Factory site, partOf, Peng Chau industrial area]
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: Peng Chau industrial area
Triple: [Old Leather Factory site, partOf, Peng Chau industrial area]
Generated description
Peng Chau industrial area is a former manufacturing district on Peng Chau Island in Hong Kong, known for its now-defunct factories and remnants of the island’s once-thriving industrial past.

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_69f76e20d65c81909619ac0dd85c56f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6bf5e3c81908cbc0e5a3744fb6b completed May 7, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7f101ec8190928a2086c54278c2 completed June 28, 2026, 11:02 p.m.
NEDg Description generation batch_6a41a8f8ff04819087c4b80f8de32b81 completed June 28, 2026, 11:06 p.m.
NED2 Entity disambiguation (via description) batch_6a41a9aecf108190a0833bde27cb0e6a completed June 28, 2026, 11:09 p.m.
Created at: May 3, 2026, 4:30 p.m.