Triple
T14195738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandinka language |
E351830
|
entity |
| Predicate | usesWordOrder |
P1249
|
FINISHED |
| Object | SOV |
—
|
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: SOV | Statement: [Mandinka language, usesWordOrder, SOV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesWordOrder Context triple: [Mandinka language, usesWordOrder, SOV]
-
A.
hasBasicWordOrder
chosen
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
-
B.
alsoExhibitsWordOrder
Indicates that one linguistic element displays the same or an additional word order pattern as another element or construction.
-
C.
hasV2WordOrder
Indicates that a clause or language follows verb-second (V2) word order, where the finite verb consistently appears in the second position of the sentence.
-
D.
usesWord
Indicates that one entity employs, contains, or makes use of a particular word in its expression, content, or communication.
-
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.
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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e1fbd48190a4864fa4443f8f29 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:04 a.m.