Triple
T35783739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 259-3 |
E1034505
|
entity |
| Predicate | scriptTransliteratedTo |
P62529
|
FINISHED |
| Object | Latin script |
—
|
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 script | Statement: [ISO 259-3, scriptTransliteratedTo, Latin script]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptTransliteratedTo Context triple: [ISO 259-3, scriptTransliteratedTo, Latin script]
-
A.
scriptTranscribedFrom
Indicates that a written script is a transcription derived from another source, such as audio, video, or a different script.
-
B.
transliterationTarget
chosen
Indicates that one entity is the target script or form into which another entity is transliterated.
-
C.
transliterationName
Indicates that one entity is the transliterated form of another entity’s name from one writing system into another.
-
D.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
-
E.
transliterationLanguage
Indicates the language whose writing system is used as the target when converting text from one script to another.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 3, 2026, 4:06 p.m.