Triple
T2858867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roro |
E63268
|
entity |
| Predicate | isCodeForUndecipheredScript |
P43702
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Roro, isCodeForUndecipheredScript, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCodeForUndecipheredScript Context triple: [Roro, isCodeForUndecipheredScript, true]
-
A.
coDecipherer
Indicates that two or more entities jointly participated in deciphering or decoding something together.
-
B.
isOfficialCodeFor
Indicates that one entity serves as the formally recognized or authorized code that designates or identifies another entity.
-
C.
scriptCodeISO15924
Indicates the script or writing system used to represent text, identified by its ISO 15924 code.
-
D.
decipheredFrom
Indicates that something has been interpreted, decoded, or understood based on information derived from another source.
-
E.
hasUnicodeScript
Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf89d3b4819086936f26d8683a2a |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 10:02 p.m.