Triple

T9460118
Position Surface form Disambiguated ID Type / Status
Subject Texas Legislative Budget Board E228122 entity
Predicate abbreviation P43 FINISHED
Object LBB
LBB is the nonpartisan legislative agency in Texas that provides budget analysis, fiscal policy recommendations, and support to the state legislature.
 E801147 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: LBB | Statement: [Texas Legislative Budget Board, abbreviation, LBB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LBB
Context triple: [Texas Legislative Budget Board, abbreviation, LBB]
  • A. LBBG
    LBBG is the ICAO airport code for Burgas Airport, an international airport serving the city of Burgas on Bulgaria’s Black Sea coast.
  • B. LBC
    LBC is a leading UK-based national talk radio station known for its news, politics, and phone-in discussion programmes.
  • C. LBN
    LBN is the three-letter ISO 3166-1 alpha-3 country code for Lebanon.
  • D. LB
    LB is the two-letter ISO 3166-1 alpha-2 country code representing Lebanon.
  • E. LB
    LB is the former New York Stock Exchange ticker symbol for L Brands, the American retail company that owned brands such as Victoria’s Secret and Bath & Body Works.
  • 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: LBB
Triple: [Texas Legislative Budget Board, abbreviation, LBB]
Generated description
LBB is the nonpartisan legislative agency in Texas that provides budget analysis, fiscal policy recommendations, and support to the state legislature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LBB
Target entity description: LBB is the nonpartisan legislative agency in Texas that provides budget analysis, fiscal policy recommendations, and support to the state legislature.
  • A. LBBG
    LBBG is the ICAO airport code for Burgas Airport, an international airport serving the city of Burgas on Bulgaria’s Black Sea coast.
  • B. LBC
    LBC is a leading UK-based national talk radio station known for its news, politics, and phone-in discussion programmes.
  • C. LBN
    LBN is the three-letter ISO 3166-1 alpha-3 country code for Lebanon.
  • D. LB
    LB is the two-letter ISO 3166-1 alpha-2 country code representing Lebanon.
  • E. LB
    LB is the vehicle registration code for the Ludwigsburg district in the Stuttgart administrative region of Baden-Württemberg, Germany.
  • 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_69ca843b123881909b0e60028475d12d completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fcaf610819092bcd3b871665aa5 completed April 1, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122965aa48190bb35202b8dd0fdbd completed April 4, 2026, 2:39 p.m.
NEDg Description generation batch_69d12474e91c8190b3f127a44fb0f345 completed April 4, 2026, 2:47 p.m.
NED2 Entity disambiguation (via description) batch_69d12521921881909fa14b99c6dd5158 completed April 4, 2026, 2:50 p.m.
Created at: March 30, 2026, 7:52 p.m.