Triple
T24583358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirionó language |
E608310
|
entity |
| Predicate | hasOralStops |
P156446
|
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, hasOralStops, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOralStops Context triple: [Sirionó language, hasOralStops, yes]
-
A.
hasOralDiscFunction
Indicates that an entity possesses a specific functional role or capability associated with its oral disc.
-
B.
isPrimarilyOral
Indicates that the primary mode of expression, communication, or transmission is spoken rather than written or signed.
-
C.
isOralFormOf
Indicates that one entity is the oral (by-mouth) dosage form or version of another entity, typically a drug or medicinal product.
-
D.
hasTypeOfMouth
Indicates that an entity possesses a mouth characterized by a specific type or form.
-
E.
hasVoicelessStops
Indicates that the subject language or sound system includes voiceless stop consonants (such as [p], [t], [k]) in its phonemic inventory.
- 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.