Triple
T12620176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | xargs |
E301356
|
entity |
| Predicate | tokenizesByDefaultOn |
P64886
|
FINISHED |
| Object | whitespace |
—
|
LITERAL 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: whitespace | Statement: [xargs, tokenizesByDefaultOn, whitespace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tokenizesByDefaultOn Context triple: [xargs, tokenizesByDefaultOn, whitespace]
-
A.
tokenizerType
Indicates the specific tokenization method or algorithm used to split text into tokens.
-
B.
isDefaultFor
chosen
Indicates that something serves as the standard or fallback option that is automatically applied or selected for a given entity or context unless another choice is explicitly specified.
-
C.
canContainToken
Indicates that one entity is capable of holding, including, or enclosing the specified token within itself.
-
D.
syntaxBasedOn
Indicates that the syntactic structure or rules of one entity are derived from, influenced by, or constructed according to the syntax of another entity.
-
E.
separatesBy
Indicates that one entity divides, partitions, or creates a boundary between two or more other entities.
- F. None of above.
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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:13 p.m.