Triple
T37673441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lugwere |
E938022
|
entity |
| Predicate | hasOrthographyStandardizationEfforts |
P199220
|
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: [Lugwere, hasOrthographyStandardizationEfforts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographyStandardizationEfforts Context triple: [Lugwere, hasOrthographyStandardizationEfforts, yes]
-
A.
hasStandardOrthographySince
Indicates that a language or writing system has used a particular standardized orthography starting from a specified point in time.
-
B.
standardizesOrthographyOf
Indicates that one entity establishes or applies a consistent writing system or spelling conventions to another entity’s language or text.
-
C.
hasOfficialOrthography
Indicates that an entity has a formally recognized and standardized system for writing its language or name.
-
D.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another entity.
-
E.
hasPhonologicalStandard
Indicates that one entity serves as the accepted or prescribed phonological norm or standard for the pronunciation system of another entity.
- 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_69f76ed7b1408190ba8c93c53cb8becf |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
| PDg | Predicate description generation | batch_69ff263632608190a99beb73608066d8 |
completed | May 9, 2026, 12:19 p.m. |
Created at: May 3, 2026, 4:18 p.m.