Triple
T17674828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BEAM virtual machine |
E440619
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object | Alpaca |
—
|
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: Alpaca | Statement: [BEAM virtual machine, supportsLanguage, Alpaca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alpaca Context triple: [BEAM virtual machine, supportsLanguage, Alpaca]
-
A.
Vicugna pacos
Vicugna pacos, commonly known as the alpaca, is a domesticated South American camelid prized for its soft, luxurious fiber and often kept in herds in the Andes.
-
B.
Llama
chosen
Llama is an open-source large language model family developed by Meta for a wide range of natural language understanding and generation tasks.
-
C.
Vicuña
Vicuña is a small Chilean town in the Elqui Valley, known for its clear skies, observatories, and production of pisco.
-
D.
Vicuña
The vicuña is a small, wild South American camelid native to the high Andes, renowned for its exceptionally fine and valuable wool.
-
E.
Guanaco
The guanaco is a wild South American camelid, closely related to the llama, known for its slender build, fine wool, and adaptation to arid and high-altitude environments.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6ba22081909e2099490c047378 |
completed | April 19, 2026, 6 a.m. |
Created at: April 10, 2026, 10 a.m.