Triple

T1454283
Position Surface form Disambiguated ID Type / Status
Subject E31362 entity
Predicate isAmongMostCommonSurnamesIn P29278 FINISHED
Object Vietnam E4138 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: Vietnam | Statement: [Lê, isAmongMostCommonSurnamesIn, Vietnam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vietnam
Context triple: [Lê, isAmongMostCommonSurnamesIn, Vietnam]
  • A. Viet Nam chosen
    Viet Nam is a Southeast Asian nation known for its rapid economic growth, rich cultural heritage, and strategic role in regional and global trade.
  • B. Democratic Republic of Vietnam
    The Democratic Republic of Vietnam was the communist state in northern Vietnam that led the struggle against the United States and South Vietnam during the Vietnam War and later unified the country under its rule.
  • C. Viet
    Viet refers to the ethnic Vietnamese people, the majority ethnic group of Vietnam with a distinct language and culture.
  • D. Cochinchina
    Cochinchina was the southern region of Vietnam that became a French colony and later formed part of French Indochina.
  • E. Laos
    Laos is a landlocked Southeast Asian country known for its mountainous terrain, Buddhist culture, and status as one of the region’s least developed but rapidly reforming economies.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c9df014081908a6e2f41ba012ecc completed March 1, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fa73fe8819097bcd6c07793bc52 completed March 9, 2026, 1:17 a.m.
Created at: March 1, 2026, 8 p.m.