Triple
T30571805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Malay |
E778139
|
entity |
| Predicate | hasUncertainDefinition |
P180254
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Proto-Malay, hasUncertainDefinition, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUncertainDefinition Context triple: [Proto-Malay, hasUncertainDefinition, yes]
-
A.
hasUncertainForm
Indicates that the form or structure of something is not clearly defined, fixed, or confidently known.
-
B.
hasUncertainNature
Indicates that the nature, status, or characteristics of the relationship or situation are not clearly defined, known, or determined.
-
C.
hasUncertainVocabulary
Indicates that the relationship involves vocabulary whose meaning, usage, or interpretation is not clearly defined or is subject to doubt.
-
D.
hasUncertainty
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
E.
hasUncertainPurpose
Indicates that the purpose or intended function of an entity, action, or relationship is unknown, ambiguous, or not clearly defined.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 29, 2026, 8:22 p.m.