Triple

T1765127
Position Surface form Disambiguated ID Type / Status
Subject Vietnam National University, Hanoi E38744 entity
Predicate abbreviation P43 FINISHED
Object VNU
VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
 E197413 NE FINISHED

How this triple was built (4 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: VNU | Statement: [Vietnam National University, Hanoi, abbreviation, VNU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VNU
Context triple: [Vietnam National University, Hanoi, abbreviation, VNU]
  • A. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • B. VN
    VN is the IATA airline designator assigned to Vietnam Airlines, the national flag carrier of Vietnam.
  • C. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • D. NBU
    NBU is the central bank of Ukraine, responsible for the country’s monetary policy, currency stability, and regulation of the banking system.
  • E. VNM
    VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: VNU
Triple: [Vietnam National University, Hanoi, abbreviation, VNU]
Generated description
VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VNU
Target entity description: VNU is a leading public research university system in Vietnam, headquartered in Hanoi and known for its comprehensive programs and high academic standards.
  • A. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • B. VN
    VN is the IATA airline designator assigned to Vietnam Airlines, the national flag carrier of Vietnam.
  • C. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • D. NBU
    NBU is the central bank of Ukraine, responsible for the country’s monetary policy, currency stability, and regulation of the banking system.
  • E. VNM
    VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
  • F. None of above. chosen

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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6467c3f08190abc8a06269ede908 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0f37a28819086c35c9f7a07dea9 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada4da6a988190847452139e1c210d completed March 8, 2026, 4:33 p.m.
NED2 Entity disambiguation (via description) batch_69ada55d96b88190a4a5c6973d69592d completed March 8, 2026, 4:35 p.m.
Created at: March 4, 2026, 7:31 p.m.