Triple
T7112450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Help America Vote Act |
E165736
|
entity |
| Predicate | hasShortName |
P1354
|
FINISHED |
| Object | HAVA |
E165736
|
NE FINISHED |
How this triple was built (2 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: HAVA | Statement: [Help America Vote Act, hasShortName, HAVA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HAVA Context triple: [Help America Vote Act, hasShortName, HAVA]
-
A.
HAVA
chosen
HAVA is the commonly used acronym for the Help America Vote Act, a U.S. federal law enacted to improve the administration and security of elections.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
HAF
HAF is the commonly used abbreviation for the Hellenic Air Force, the air warfare branch of Greece’s armed forces.
-
D.
Haise
Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
-
E.
Havins
Havins is a surname most notably associated with American actress Alexa Havins.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c6e5edf89c8190a069b35ff7768165 |
completed | March 27, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a325a07c81909bd9a8f5d4461fb9 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:43 p.m.