Triple
T34261542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Siouan language |
E879043
|
entity |
| Predicate | studiedInSubfield |
P170087
|
FINISHED |
| Object | Siouan linguistics |
—
|
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: Siouan linguistics | Statement: [Proto-Siouan language, studiedInSubfield, Siouan linguistics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiedInSubfield Context triple: [Proto-Siouan language, studiedInSubfield, Siouan linguistics]
-
A.
studiedInSubdiscipline
chosen
Indicates that an entity pursued study or academic work within a specific subdiscipline of a broader field.
-
B.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
C.
isPartOfStudyField
Indicates that one subject, topic, or subfield belongs to, is included within, or is a component of a broader academic or research field.
-
D.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
E.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.