Triple
T36631371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara–Bagirmi languages |
E904325
|
entity |
| Predicate | haveSVOOrder |
P27272
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sara–Bagirmi languages, haveSVOOrder, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveSVOOrder Context triple: [Sara–Bagirmi languages, haveSVOOrder, true]
-
A.
hasSVOOrder
chosen
Indicates that a language or construction follows a basic word order where the subject comes first, followed by the verb, and then the object.
-
B.
hasSVOAlternativeOrder
Indicates that there exists an alternative Subject–Verb–Object word order for expressing the same proposition or relation.
-
C.
hasOrder
Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
-
D.
SOVOrderPossible
Indicates that a subject–object–verb (SOV) word order is grammatically possible in the language or construction being described.
-
E.
hasVSOOrderVariant
Indicates that a language has a variant word order pattern in which clauses can appear in Verb–Subject–Object (VSO) order.
- 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_69f76e6c63e48190b1d0c3a79a6c7406 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.