Triple

T7111092
Position Surface form Disambiguated ID Type / Status
Subject Family Smoking Prevention and Tobacco Control Act of 2009 E165707 entity
Predicate acronym P43 FINISHED
Object TCA
TCA is the commonly used abbreviation for the Family Smoking Prevention and Tobacco Control Act of 2009, a U.S. law granting the FDA authority to regulate tobacco products.
 E642130 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: TCA | Statement: [Family Smoking Prevention and Tobacco Control Act of 2009, acronym, TCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TCA
Context triple: [Family Smoking Prevention and Tobacco Control Act of 2009, acronym, TCA]
  • A. TCA
    TCA is the three-letter ISO 3166-1 alpha-3 country code for the Turks and Caicos Islands.
  • B. TCA
    TCA is the IATA airport code for Tennant Creek Airport in Australia’s Northern Territory.
  • C. TCA
    TCA is a prominent multidisciplinary arts and performance venue located in Tempe, Arizona.
  • D. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • E. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • 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: TCA
Triple: [Family Smoking Prevention and Tobacco Control Act of 2009, acronym, TCA]
Generated description
TCA is the commonly used abbreviation for the Family Smoking Prevention and Tobacco Control Act of 2009, a U.S. law granting the FDA authority to regulate tobacco products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TCA
Target entity description: TCA is the commonly used abbreviation for the Family Smoking Prevention and Tobacco Control Act of 2009, a U.S. law granting the FDA authority to regulate tobacco products.
  • A. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • B. TCA
    TCA is the three-letter ISO 3166-1 alpha-3 country code for the Turks and Caicos Islands.
  • C. TCA
    TCA is the IATA airport code for Tennant Creek Airport in Australia’s Northern Territory.
  • D. TCA
    TCA is a prominent multidisciplinary arts and performance venue located in Tempe, Arizona.
  • E. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • 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_69c6888120f081908f8f01b201dc4a4c completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5ecd4488190bf19e42de55da98b completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79cb8d4988190945516cee5d6d53b completed March 28, 2026, 9:17 a.m.
NEDg Description generation batch_69c79d3feacc819097887064a7439340 completed March 28, 2026, 9:20 a.m.
NED2 Entity disambiguation (via description) batch_69c79df3f5648190981176b6c9791181 completed March 28, 2026, 9:23 a.m.
Created at: March 27, 2026, 2:43 p.m.