Triple

T24254527
Position Surface form Disambiguated ID Type / Status
Subject Ngô Tất Tố E603630 entity
Predicate givenName P17 FINISHED
Object Tất Tố
Tất Tố is the given name of Ngô Tất Tố, a prominent early 20th-century Vietnamese writer, journalist, and social critic known for his realist literature and advocacy for peasants.
E1624948 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: Tất Tố | Statement: [Ngô Tất Tố, givenName, Tất Tố]
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: Tất Tố
Triple: [Ngô Tất Tố, givenName, Tất Tố]
Generated description
Tất Tố is the given name of Ngô Tất Tố, a prominent early 20th-century Vietnamese writer, journalist, and social critic known for his realist literature and advocacy for peasants.

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_69e29540da0481909a38bdae315b7a02 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28b8ca4988190b565c2873dc6559d completed April 29, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd3b72508190955c8da4c9a5d0b8 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbf90cb488190acfdf236e2b28338 completed May 22, 2026, 2:29 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc06a9f2481909c0e770b96664781 completed May 22, 2026, 2:33 a.m.
Created at: April 18, 2026, 12:05 a.m.