Triple

T6239304
Position Surface form Disambiguated ID Type / Status
Subject Broken Arrow, Oklahoma E139558 entity
Predicate hasNickname P39 FINISHED
Object BA
BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
 E577642 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: [Broken Arrow, Oklahoma, hasNickname, BA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BA
Context triple: [Broken Arrow, Oklahoma, hasNickname, 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: [Broken Arrow, Oklahoma, hasNickname, BA]
Generated description
BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BA
Target entity description: BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
  • 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 commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • C. 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.
  • D. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • E. BA
    BA is the IATA code for British Airways, the United Kingdom’s flag carrier and one of the world’s largest international airlines.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063048df081909a13d16b6f6bf65d completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20e01845081909c54fe938600be3e completed March 24, 2026, 4:07 a.m.
NEDg Description generation batch_69c215ff293c8190a79dd9246c38880d completed March 24, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69c2167ef4748190bebcf28468a696bc completed March 24, 2026, 4:43 a.m.
Created at: March 22, 2026, 4:23 p.m.