Triple
T4218448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sac and Fox language |
E94278
|
entity |
| Predicate | languageTypology |
P5201
|
FINISHED |
| Object | polysynthetic language |
—
|
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: polysynthetic language | Statement: [Sac and Fox language, languageTypology, polysynthetic language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageTypology Context triple: [Sac and Fox language, languageTypology, polysynthetic language]
-
A.
linguisticClassification
Indicates the relationship by which an entity is categorized according to its language or linguistic type.
-
B.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
C.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
D.
hasLinguisticTypology
chosen
Indicates a relationship where a language or linguistic system is characterized by a specific typological classification or structural type.
-
E.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.