Triple
T29440127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archins |
E746687
|
entity |
| Predicate | hasLanguageWithRichMorphology |
P7162
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Archins, hasLanguageWithRichMorphology, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageWithRichMorphology Context triple: [Archins, hasLanguageWithRichMorphology, true]
-
A.
isInflectedLanguage
Indicates that a language uses systematic changes in word form (inflections) to express grammatical categories such as tense, case, number, or gender.
-
B.
hasVerbalMorphology
Indicates that one linguistic element exhibits verbal inflectional properties or patterns in relation to another.
-
C.
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.
-
D.
hasLinguisticFeature
chosen
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
E.
hasMorphosyntax
Indicates a relationship where an entity is associated with, characterized by, or analyzed in terms of its morphological and syntactic structure.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: April 28, 2026, 3:21 p.m.