Triple
T4328723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triskelion of Mann |
E96693
|
entity |
| Predicate | writingSystemOnMotto |
P454
|
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: [Triskelion of Mann, writingSystemOnMotto, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingSystemOnMotto Context triple: [Triskelion of Mann, writingSystemOnMotto, Latin alphabet]
-
A.
languageOfMotto
Indicates the language in which a motto is written or expressed.
-
B.
writingSystemUsedIn
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
C.
mottoOriginalLanguage
Indicates the language in which a motto was originally formulated or expressed.
-
D.
writingSystem
chosen
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
E.
mottoTransliteration
Indicates the representation of a motto’s original text using the characters of another writing system (its transliteration).
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35133688c8190ab5527ae01748f13 |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4e13fc8190a42c519f37959d27 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:13 p.m.