Triple
T23957909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakao language |
E603846
|
entity |
| Predicate | hasValencyOperation |
P154512
|
FINISHED |
| Object | causative |
—
|
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: causative | Statement: [Sakao language, hasValencyOperation, causative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasValencyOperation Context triple: [Sakao language, hasValencyOperation, causative]
-
A.
hasOperationsIn
Indicates that an entity conducts business activities or maintains operational presence within a specified location or region.
-
B.
hasConjugationOperation
Indicates that there exists an operation that transforms an entity into its conjugate form (e.g., algebraic, complex, or grammatical conjugation).
-
C.
hasOperationType
Indicates the specific kind or category of operation associated with an entity or process.
-
D.
hasBinaryOperation
Indicates that there exists a binary operation defined on the related entity or between the related entities, combining two inputs to produce a single output.
-
E.
hasMainOperations
Indicates that an entity is associated with its primary or core operations, activities, or functions.
- F. None of above. chosen
Provenance (4 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_69e2954222288190a7323554d0cca8d7 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d0d85d348190946b578e1a1c3bcc |
completed | April 29, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:22 p.m.