Triple
T21053849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zigula language |
E518656
|
entity |
| Predicate | subjectVerbObjectOrder |
P1249
|
FINISHED |
| Object | SVO (subject–verb–object) word order |
—
|
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: SVO (subject–verb–object) word order | Statement: [Zigula language, subjectVerbObjectOrder, SVO (subject–verb–object) word order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectVerbObjectOrder Context triple: [Zigula language, subjectVerbObjectOrder, SVO (subject–verb–object) word order]
-
A.
objectOfVerb
Indicates that one entity serves as the direct object or recipient of the action expressed by a given verb in a clause.
-
B.
alsoExhibitsWordOrder
Indicates that one linguistic element displays the same or an additional word order pattern as another element or construction.
-
C.
hasSubjectPosition
Indicates that an entity occupies or is assigned to a particular subject role or position within a structure, context, or organization.
-
D.
SOVOrderPossible
Indicates that a subject–object–verb (SOV) word order is grammatically possible in the language or construction being described.
-
E.
hasBasicWordOrder
chosen
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7e087c81908712ddc63e8b1e6c |
completed | April 21, 2026, 4:30 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:36 p.m.