Triple

T526482
Position Surface form Disambiguated ID Type / Status
Subject Immigration and Nationality Act E10929 entity
Predicate shortName P43 FINISHED
Object INA
INA is the commonly used abbreviation for the U.S. Immigration and Nationality Act, the foundational federal law governing immigration and citizenship in the United States.
 E65816 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: INA | Statement: [Immigration and Nationality Act, shortName, INA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: INA
Context triple: [Immigration and Nationality Act, shortName, INA]
  • A. NI
    NI is the vehicle registration code used on license plates for the German federal state of Lower Saxony.
  • B. IN
    IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
  • C. IL
    IL is the two-letter ISO 3166-1 alpha-2 country code assigned to Israel for international standardization and data representation.
  • D. IND
    IND is the abbreviated name commonly used for the Industriales baseball team, one of the most popular and successful clubs in Cuban baseball.
  • E. NIA
    NIA is a U.S. federal research institute within the National Institutes of Health that focuses on understanding aging and age-related diseases, including Alzheimer’s disease.
  • 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: INA
Triple: [Immigration and Nationality Act, shortName, INA]
Generated description
INA is the commonly used abbreviation for the U.S. Immigration and Nationality Act, the foundational federal law governing immigration and citizenship in the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: INA
Target entity description: INA is the commonly used abbreviation for the U.S. Immigration and Nationality Act, the foundational federal law governing immigration and citizenship in the United States.
  • A. NI
    NI is the vehicle registration code used on license plates for the German federal state of Lower Saxony.
  • B. IN
    IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
  • C. IL
    IL is the two-letter ISO 3166-1 alpha-2 country code assigned to Israel for international standardization and data representation.
  • D. IND
    IND is the abbreviated name commonly used for the Industriales baseball team, one of the most popular and successful clubs in Cuban baseball.
  • E. NIA
    NIA is a U.S. federal research institute within the National Institutes of Health that focuses on understanding aging and age-related diseases, including Alzheimer’s disease.
  • 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_69a2e84b16c4819088d284c47c3a7968 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1d0d22081908aad915482d39e74 completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b24157608190b4c7df2cae453a1f completed March 1, 2026, 9:40 p.m.
NEDg Description generation batch_69a4b4117f60819093b6eed4e9eb4630 completed March 1, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69a4b476ecc881909ff7efbb3299ace3 completed March 1, 2026, 9:49 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.