Triple
T20614915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VRG |
E506540
|
entity |
| Predicate | designates |
P974
|
FINISHED |
| Object | Varig |
—
|
NE NERFINISHED |
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: Varig | Statement: [VRG, designates, Varig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varig Context triple: [VRG, designates, Varig]
-
A.
Varig
chosen
Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
-
B.
Varpas
Varpas was a Lithuanian national revival periodical that played a key role in promoting Lithuanian language, culture, and political awareness in the late 19th century.
-
C.
Vara
Vara is a short form of the female given name Varvara, commonly used in Slavic languages.
-
D.
Vara
Vara is a small locality and municipality in western Sweden known for its agricultural landscape and rural character.
-
E.
Varia
Varia is a village on the island of Lesbos in Greece, known for hosting the Tériade Museum of Modern Art.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aadaf47881909e93efb535c6c1e3 |
completed | April 20, 2026, 10:38 p.m. |
Created at: April 16, 2026, 11:41 a.m.