Triple

T2953791
Position Surface form Disambiguated ID Type / Status
Subject Economic Recovery Tax Act of 1981 E79882 entity
Predicate alsoKnownAs P39 FINISHED
Object ERTA
ERTA is a landmark 1981 U.S. federal law that significantly reduced individual and business income taxes to stimulate economic growth during the Reagan administration.
 E315160 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: ERTA | Statement: [Economic Recovery Tax Act of 1981, alsoKnownAs, ERTA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ERTA
Context triple: [Economic Recovery Tax Act of 1981, alsoKnownAs, ERTA]
  • A. ERT
    ERT is an acronym commonly used to refer to an Emergency Response Team, a specialized group trained to react quickly and effectively to crises or hazardous incidents.
  • B. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • C. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • D. ETA
    ETA is a U.S. Department of Labor agency that oversees federal employment, job training, and workforce development programs.
  • E. ERL
    ERL is a research facility focused on studying and developing technologies for the exploration, monitoring, and management of Earth's natural resources.
  • 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: ERTA
Triple: [Economic Recovery Tax Act of 1981, alsoKnownAs, ERTA]
Generated description
ERTA is a landmark 1981 U.S. federal law that significantly reduced individual and business income taxes to stimulate economic growth during the Reagan administration.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ERTA
Target entity description: ERTA is a landmark 1981 U.S. federal law that significantly reduced individual and business income taxes to stimulate economic growth during the Reagan administration.
  • A. ERT
    ERT is an acronym commonly used to refer to an Emergency Response Team, a specialized group trained to react quickly and effectively to crises or hazardous incidents.
  • B. ETB
    ETB is the three-letter international currency code used to represent the Ethiopian birr in global financial and foreign exchange contexts.
  • C. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • D. ETA
    ETA is a U.S. Department of Labor agency that oversees federal employment, job training, and workforce development programs.
  • E. ERL
    ERL is a research facility focused on studying and developing technologies for the exploration, monitoring, and management of Earth's natural resources.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98ff874c81908077a90fdc5e8549 completed March 8, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc82d1248190869beffffc0bf956 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b0fd25e07c819088b2b1bcef4cf54e completed March 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69b100ecbee081908832ddec0efdc751 completed March 11, 2026, 5:43 a.m.
Created at: March 8, 2026, 2:57 p.m.