Triple
T26096540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cia-Cia |
E658283
|
entity |
| Predicate | usesLatinOrthography |
P163866
|
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: [Cia-Cia, usesLatinOrthography, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLatinOrthography Context triple: [Cia-Cia, usesLatinOrthography, yes]
-
A.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another entity.
-
B.
usesLatinAlphabetSince
Indicates that an entity has employed the Latin alphabet as its writing system starting from a specific point in time and continuing thereafter.
-
C.
hasOrthographicConvention
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
-
D.
usesDiacriticsFrom
Indicates that one entity employs or incorporates the diacritical marks that originate from or are characteristic of another entity.
-
E.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
- 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_69ee5bbfc4d08190a1b206d0ac3a1e8d |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 26, 2026, 7:51 p.m.