Triple
T6776985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apurinã language |
E155581
|
entity |
| Predicate | hasPartOfSpeechSystem |
P7162
|
FINISHED |
| Object | rich verbal system |
—
|
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: rich verbal system | Statement: [Apurinã language, hasPartOfSpeechSystem, rich verbal system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartOfSpeechSystem Context triple: [Apurinã language, hasPartOfSpeechSystem, rich verbal system]
-
A.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
B.
partOfLanguage
Indicates that one linguistic element belongs to, is included within, or is a component of a particular language.
-
C.
hasPunctuationSystem
Indicates that an entity possesses or employs a system of punctuation marks for structuring written language.
-
D.
hasPronounSystem
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
-
E.
hasLinguisticFeature
chosen
Indicates that an entity possesses a particular linguistic property, trait, 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26725208190b64935cfd08b2aff |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.