Triple
T11742634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiricahua language |
E279192
|
entity |
| Predicate | primaryWordOrderTendency |
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: [Chiricahua language, primaryWordOrderTendency, SOV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWordOrderTendency Context triple: [Chiricahua language, primaryWordOrderTendency, 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.
primaryGrammaticalBasis
Indicates that one element serves as the main grammatical foundation or core structure upon which another linguistic element is based or constructed.
-
C.
usesPostpositions
Indicates that one entity employs postpositions, placing relational or grammatical markers after the words they modify rather than before them.
-
D.
typicalPositionInSentence
Indicates the usual or most common position that an element occupies within the linear order of components in a sentence.
-
E.
firstWord
Indicates that one entity is the first word in the sequence or text associated with another entity.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f191388190bd6ef7e80c41ca48 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.