Triple
T20691016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roko Tui Dreketi |
E508548
|
entity |
| Predicate | titleLanguageScript |
P63723
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [Roko Tui Dreketi, titleLanguageScript, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleLanguageScript Context triple: [Roko Tui Dreketi, titleLanguageScript, Latin alphabet]
-
A.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
B.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
-
C.
nativeNameScript
chosen
Indicates the writing system or script in which an entity’s native name is expressed.
-
D.
titleLanguageForm
Indicates the specific linguistic form or variant in which a title is expressed (e.g., language, script, or transliteration form).
-
E.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10d83548190a52b9ef84c8f9205 |
completed | April 21, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:08 p.m.