Triple
T25527428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahasa Samawa |
E639811
|
entity |
| Predicate | usesAffixation |
P159453
|
FINISHED |
| Object | prefixes |
—
|
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: prefixes | Statement: [Bahasa Samawa, usesAffixation, prefixes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAffixation Context triple: [Bahasa Samawa, usesAffixation, prefixes]
-
A.
hasDerivationalAffixes
Indicates that one linguistic form is related to another by the addition of derivational affixes that change its grammatical category or meaning.
-
B.
hasPossessiveAffixes
Indicates that an entity (typically a word or morpheme) carries affixes that mark grammatical possession or ownership.
-
C.
inflectionOf
Indicates that one linguistic form is an inflected variant of another base or lemma form.
-
D.
usedAsSuffixTo
Indicates that one entity functions as a suffix appended to another entity, typically to modify or extend its meaning.
-
E.
usesPostpositions
Indicates that one entity employs postpositions, placing relational or grammatical markers after the words they modify rather than before them.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f86073d0819093afb1d79b97bccc |
completed | May 2, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 21, 2026, 3:11 p.m.