Triple

T26541622
Position Surface form Disambiguated ID Type / Status
Subject Taiwan Solidarity Union E671403 entity
Predicate founder P104 FINISHED
Object Huang Chu-wen
Huang Chu-wen is a Taiwanese politician known for his leadership roles in pro-Taiwanese identity politics and his influence in the island’s post-martial-law democratic era.
E1749420 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: Huang Chu-wen | Statement: [Taiwan Solidarity Union, founder, Huang Chu-wen]
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: Huang Chu-wen
Triple: [Taiwan Solidarity Union, founder, Huang Chu-wen]
Generated description
Huang Chu-wen is a Taiwanese politician known for his leadership roles in pro-Taiwanese identity politics and his influence in the island’s post-martial-law democratic era.

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_69eeb3206e748190b90c85cc81f38c91 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61431eb008190affb2b34864b3e8a completed May 2, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a122975869881909eda4cc30c4f42e1 completed May 23, 2026, 10:25 p.m.
NEDg Description generation batch_6a122a2048408190a3a8cf5a2efa9b08 completed May 23, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_6a122ac1713481909a80761bb471ef49 completed May 23, 2026, 10:31 p.m.
Created at: April 27, 2026, 1:42 a.m.