Triple

T31909464
Position Surface form Disambiguated ID Type / Status
Subject Ba Jin E814640 entity
Predicate notableWork P4 FINISHED
Object The Torrents Trilogy
The Torrents Trilogy is a renowned series of semi-autobiographical Chinese novels by Ba Jin that critically portrays traditional family structures and social upheaval in early 20th-century China.
E1982285 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: The Torrents Trilogy | Statement: [Ba Jin, notableWork, The Torrents Trilogy]
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: The Torrents Trilogy
Triple: [Ba Jin, notableWork, The Torrents Trilogy]
Generated description
The Torrents Trilogy is a renowned series of semi-autobiographical Chinese novels by Ba Jin that critically portrays traditional family structures and social upheaval in early 20th-century China.

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_69f348f109d88190b5005372c53d2fcd completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b1b92b9081909105e14626a3c04b completed May 3, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7ff95714819091e86d6f263a04c9 completed June 14, 2026, 10:18 a.m.
NEDg Description generation batch_6a2e80a633308190a46794c5d992993c completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e817feee48190a55b72e9901e1ba6 completed June 14, 2026, 10:25 a.m.
Created at: May 1, 2026, 12:01 a.m.