Triple
T7093636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genetic Information Nondiscrimination Act of 2008 |
E165266
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
GINA
GINA is a U.S. federal law that prohibits discrimination in health insurance and employment based on an individual’s genetic information.
|
E642292
|
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: GINA | Statement: [Genetic Information Nondiscrimination Act of 2008, shortName, GINA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GINA Context triple: [Genetic Information Nondiscrimination Act of 2008, shortName, GINA]
-
A.
GIN
GIN is the three-letter ISO 3166-1 alpha-3 country code assigned to the West African nation of Guinea.
-
B.
Gina
Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
-
C.
Gingins
Gingins is a small Swiss municipality in the canton of Vaud, located near the Jura Mountains and Lake Geneva.
-
D.
GAS
GAS (GNU Assembler) is the assembler component of the GNU toolchain, used to translate assembly language code into machine code for various computer architectures.
-
E.
GCA
GCA is a landmark U.S. federal law enacted in 1968 that regulates the firearms industry and gun sales, including licensing, prohibited persons, and interstate commerce in weapons.
- 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: GINA Triple: [Genetic Information Nondiscrimination Act of 2008, shortName, GINA]
Generated description
GINA is a U.S. federal law that prohibits discrimination in health insurance and employment based on an individual’s genetic information.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GINA Target entity description: GINA is a U.S. federal law that prohibits discrimination in health insurance and employment based on an individual’s genetic information.
-
A.
GIN
GIN is the three-letter ISO 3166-1 alpha-3 country code assigned to the West African nation of Guinea.
-
B.
Gina
Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
-
C.
Gingins
Gingins is a small Swiss municipality in the canton of Vaud, located near the Jura Mountains and Lake Geneva.
-
D.
GAS
GAS (GNU Assembler) is the assembler component of the GNU toolchain, used to translate assembly language code into machine code for various computer architectures.
-
E.
GCA
GCA is a landmark U.S. federal law enacted in 1968 that regulates the firearms industry and gun sales, including licensing, prohibited persons, and interstate commerce in weapons.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e55159848190a794ad77e60c5525 |
completed | March 27, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c9adce081908b571c64e5d8222f |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79dab5690819094f6d8ad49e6eec5 |
completed | March 28, 2026, 9:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79e12a40c8190b21128e17c3e212e |
completed | March 28, 2026, 9:23 a.m. |
Created at: March 27, 2026, 2:41 p.m.