Triple
T9011379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yukpa language |
E215479
|
entity |
| Predicate | hasVerbalAffixes |
P48763
|
FINISHED |
| Object | person marking |
—
|
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: person marking | Statement: [Yukpa language, hasVerbalAffixes, person marking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerbalAffixes Context triple: [Yukpa language, hasVerbalAffixes, person marking]
-
A.
hasVerbalMorphology
Indicates that one linguistic element exhibits verbal inflectional properties or patterns in relation to another.
-
B.
hasVerbalFeature
chosen
Indicates that an entity possesses a specific verbal property, characteristic, or behavior related to speech or language.
-
C.
hasVerbAspect
Indicates that a verb or verbal expression is associated with a particular grammatical aspect (such as perfective, imperfective, or progressive) describing the temporal structure of the action or state.
-
D.
hasVerbalSystem
Indicates that an entity possesses or is characterized by a particular system of verbal or spoken language forms and structures.
-
E.
hasInfinitiveVerbEnding
Indicates that a verb takes the infinitive form with a specific infinitive verb ending (such as “-to” in English or “-en” in German).
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c1571881908d0b144786b5ee1f |
completed | April 1, 2026, 12:41 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:06 p.m.