Triple

T1311373
Position Surface form Disambiguated ID Type / Status
Subject Vanuatu E27996 entity
Predicate ISO3166-1Alpha3 P189 FINISHED
Object VUT
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
 E151531 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: VUT | Statement: [Vanuatu, ISO3166-1Alpha3, VUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VUT
Context triple: [Vanuatu, ISO3166-1Alpha3, VUT]
  • 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. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • C. VT
    VT is the standard two-letter postal abbreviation used to represent the U.S. state of Vermont.
  • D. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • E. VGIK
    VGIK is Russia’s renowned national film school and one of the world’s oldest film institutes, known for training influential filmmakers such as Sergei Eisenstein.
  • 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: VUT
Triple: [Vanuatu, ISO3166-1Alpha3, VUT]
Generated description
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VUT
Target entity description: VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • 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. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • C. VT
    VT is the standard two-letter postal abbreviation used to represent the U.S. state of Vermont.
  • D. V.
    V. is Thomas Pynchon's 1963 debut novel, a complex, postmodern work that interweaves multiple narratives and historical periods in a quest surrounding the mysterious figure or concept known only as "V."
  • E. VGIK
    VGIK is Russia’s renowned national film school and one of the world’s oldest film institutes, known for training influential filmmakers such as Sergei Eisenstein.
  • 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c1560f888190bdd9107b08395e0b completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf2964048190950723487c7cf707 completed March 8, 2026, 12:13 a.m.
NEDg Description generation batch_69acbfc03f20819089a025fc745c9203 completed March 8, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_69acc0282080819087676813c2852a96 completed March 8, 2026, 12:17 a.m.
Created at: March 1, 2026, 7:51 p.m.