Triple

T12899159
Position Surface form Disambiguated ID Type / Status
Subject pdfTeX E308571 entity
Predicate developer P73 FINISHED
Object Hàn Thế Thành E1008095 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: Hàn Thế Thành | Statement: [pdfTeX, developer, Hàn Thế Thành]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hàn Thế Thành
Context triple: [pdfTeX, developer, Hàn Thế Thành]
  • A. Hàn Thế Thành chosen
    Hàn Thế Thành is a Vietnamese computer scientist best known for developing pdfTeX, an extended version of TeX that outputs PDF directly.
  • B. Pham Hung
    Pham Hung was a Vietnamese communist revolutionary and politician who served as Prime Minister of Vietnam in the late 1980s.
  • C. Nguyễn Thanh Hưng
    Nguyễn Thanh Hưng is a Vietnamese professional known as a graduate of the prestigious Foreign Trade University, often associated with careers in business, economics, or international trade.
  • D. Ngo Kien Huy
    Ngo Kien Huy is a Vietnamese pop singer, actor, and television host known for his energetic performances and appearances in popular entertainment shows.
  • E. Ngo Tuan Anh
    Ngo Tuan Anh is a Vietnamese individual notable enough to be recognized as a prominent bearer of the surname Ngo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9717f3fc48190b61c8f6f36cd0725 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af59f3cc81908c99bcde43e724e6 completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:40 p.m.