Triple

T23940643
Position Surface form Disambiguated ID Type / Status
Subject New Poetry Movement E602771 entity
Predicate hasNotablePoet P4290 FINISHED
Object Nguyễn Bính
Nguyễn Bính was a prominent Vietnamese poet renowned for blending folk sensibilities with modernist themes and is often associated with the New Poetry Movement of the early 20th century.
E1630008 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: Nguyễn Bính | Statement: [New Poetry Movement, hasNotablePoet, Nguyễn Bính]
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: Nguyễn Bính
Triple: [New Poetry Movement, hasNotablePoet, Nguyễn Bính]
Generated description
Nguyễn Bính was a prominent Vietnamese poet renowned for blending folk sensibilities with modernist themes and is often associated with the New Poetry Movement of the early 20th century.

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_69e2953cf6e081909b8e25a10a52dddc completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d02a1b308190a2d101774b455417 completed April 29, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9968b8081908dc5ea2be0f2e9c7 completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcf6a9da08190889bebd86fa3184d completed May 22, 2026, 3:37 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcfd646a0819090262a17c3d05be9 completed May 22, 2026, 3:39 a.m.
Created at: April 17, 2026, 9:09 p.m.