Triple

T2069468
Position Surface form Disambiguated ID Type / Status
Subject Upper Franconia E45981 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object BA
BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
 E230928 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: BA | Statement: [Upper Franconia, hasVehicleRegistrationCode, BA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BA
Context triple: [Upper Franconia, hasVehicleRegistrationCode, BA]
  • A. BA
    BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • B. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • C. BA
    BA is the two-letter ISO 3166-1 alpha-2 country code assigned to Bosnia and Herzegovina.
  • D. BA
    BA is the commonly used abbreviation for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
  • E. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • 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: BA
Triple: [Upper Franconia, hasVehicleRegistrationCode, BA]
Generated description
BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BA
Target entity description: BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
  • A. BA
    BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • B. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • C. BA
    BA is the two-letter ISO 3166-1 alpha-2 country code assigned to Bosnia and Herzegovina.
  • D. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • E. BA
    BA is the commonly used abbreviation for the British Association for the Advancement of Science, a historic organization dedicated to promoting science and its understanding.
  • 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_69a8891b38288190abd572ccad9b6928 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9f51a008190aead0173a9289204 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae27289eb081909bfbc9bf2cd14878 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae28c163088190818891302f7faa8e completed March 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae292a9d7481909acbc3a5f24ff0b9 completed March 9, 2026, 1:58 a.m.
Created at: March 4, 2026, 7:41 p.m.