Triple
T24583343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirionó language |
E608310
|
entity |
| Predicate | hasDerivationalAffixes |
P156445
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sirionó language, hasDerivationalAffixes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDerivationalAffixes Context triple: [Sirionó language, hasDerivationalAffixes, yes]
-
A.
hasPossessiveAffixes
Indicates that an entity (typically a word or morpheme) carries affixes that mark grammatical possession or ownership.
-
B.
hasVerbalSuffixes
Indicates that a language, word, or grammatical form possesses specific suffixes that are attached to verbs.
-
C.
hasMeaningByDerivation
Indicates that the meaning of one entity is obtained or derived from another entity, rather than being original or independent.
-
D.
hasMorphosyntacticBasis
Indicates that one linguistic element’s form or syntactic behavior is grounded in, derived from, or systematically determined by another element’s morphosyntactic properties.
-
E.
hasRootWord
Indicates that one linguistic form is derived from, based on, or directly associated with a specified root word.
- F. None of above. chosen
Provenance (4 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a984577881908c855f5e05756909 |
completed | April 30, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:29 a.m.