Triple
T930503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SECVA |
E20080
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | SECVA |
E20080
|
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: SECVA | Statement: [SECVA, hasAbbreviation, SECVA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SECVA Context triple: [SECVA, hasAbbreviation, SECVA]
-
A.
SECVA
chosen
SECVA is the official acronym for the United States Secretary of Veterans Affairs, the Cabinet-level official who leads the Department of Veterans Affairs.
-
B.
SVC
SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
-
C.
CAVC
CAVC is a specialized federal court that reviews decisions made by the U.S. Department of Veterans Affairs on veterans’ benefits claims.
-
D.
SCSE
SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
-
E.
SEC West
SEC West is one of the two football divisions of the NCAA’s Southeastern Conference, featuring prominent powerhouse programs in the western portion of the league.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7ee1108188190a26c73864c697061 |
completed | March 4, 2026, 8:32 a.m. |
Created at: March 1, 2026, 7:40 p.m.