Triple

T656646
Position Surface form Disambiguated ID Type / Status
Subject Tunis E11662 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object TU
TU is the international vehicle registration code assigned to Tunisia.
E82108 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: TU | Statement: [Tunis, vehicleRegistrationCode, TU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TU
Context triple: [Tunis, vehicleRegistrationCode, TU]
  • A. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • B. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • C. UA
    UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
  • D. UA
    UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
  • E. TB
    TB is the standard abbreviation for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
  • 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: TU
Triple: [Tunis, vehicleRegistrationCode, TU]
Generated description
TU is the international vehicle registration code assigned to Tunisia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TU
Target entity description: TU is the international vehicle registration code assigned to Tunisia.
  • A. TW
    TW is the two-letter ISO 3166 country code assigned to Taiwan (commonly referred to as Chinese Taipei in certain international contexts).
  • B. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • C. UA
    UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
  • D. UA
    UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
  • E. TB
    TB is the standard abbreviation for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4e87408190b5276d2b913d0426 completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5914abe2c8190a27f520f445554d8 completed March 2, 2026, 1:31 p.m.
NEDg Description generation batch_69a5ab066d348190bbe5956cce0407ef completed March 2, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_69a5c240eebc819098cd79447ed95b08 completed March 2, 2026, 5 p.m.
Created at: March 1, 2026, 7:36 p.m.