Triple

T30878249
Position Surface form Disambiguated ID Type / Status
Subject Zhou Zuoren E786536 entity
Predicate alternativeName P39 FINISHED
Object Chou Tso-jen
Chou Tso-jen is a prominent Chinese writer, essayist, and literary critic of the early 20th century, known for his role in modern Chinese literature and as the younger brother of Lu Xun.
E2047284 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: Chou Tso-jen | Statement: [Zhou Zuoren, alternativeName, Chou Tso-jen]
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: Chou Tso-jen
Triple: [Zhou Zuoren, alternativeName, Chou Tso-jen]
Generated description
Chou Tso-jen is a prominent Chinese writer, essayist, and literary critic of the early 20th century, known for his role in modern Chinese literature and as the younger brother of Lu Xun.

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_69f224bae17c8190bb3a6a28e3d019df completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f691d87f788190bee65deb3a59057f completed May 3, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3551db13208190a8e92013cba23a31 completed June 19, 2026, 2:27 p.m.
NEDg Description generation batch_6a35557e432c8190be26b60554de5003 completed June 19, 2026, 2:43 p.m.
NED2 Entity disambiguation (via description) batch_6a3555d85d7c8190bdac94215380ab94 completed June 19, 2026, 2:44 p.m.
Created at: April 29, 2026, 8:48 p.m.