Triple

T29975517
Position Surface form Disambiguated ID Type / Status
Subject Alfred Sung E761433 entity
Predicate notableWork P4 FINISHED
Object Alfred Sung womenswear collections
Alfred Sung womenswear collections are a line of elegant, minimalist women’s clothing known for their clean tailoring, timeless silhouettes, and accessible luxury aesthetic.
 E1895078 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: Alfred Sung womenswear collections | Statement: [Alfred Sung, notableWork, Alfred Sung womenswear collections]
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: Alfred Sung womenswear collections
Triple: [Alfred Sung, notableWork, Alfred Sung womenswear collections]
Generated description
Alfred Sung womenswear collections are a line of elegant, minimalist women’s clothing known for their clean tailoring, timeless silhouettes, and accessible luxury aesthetic.

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_69f22467626081908d5afea489590e96 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f678d44b848190a0c7887baf01b905 completed May 2, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721f9890c81909812187eb4724936 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a2722c1fef08190bc0a58382ea0b6ce completed June 8, 2026, 8:14 p.m.
NED2 Entity disambiguation (via description) batch_6a2725dc8a3c8190b5a206224edfbba0 completed June 8, 2026, 8:28 p.m.
Created at: April 29, 2026, 6:33 p.m.