Triple
T25453622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dhives Akuru |
E637853
|
entity |
| Predicate | hasScriptCodeStatus |
P161649
|
FINISHED |
| Object | no ISO 15924 code as of 2024 |
—
|
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: no ISO 15924 code as of 2024 | Statement: [Dhives Akuru, hasScriptCodeStatus, no ISO 15924 code as of 2024]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScriptCodeStatus Context triple: [Dhives Akuru, hasScriptCodeStatus, no ISO 15924 code as of 2024]
-
A.
hasScriptStatus
Indicates that an entity has a particular script-related state or condition, such as whether a script is present, active, or in a given status.
-
B.
hasScriptCode
Indicates that an entity is associated with a particular writing system identified by a specific script code.
-
C.
containsScript
Indicates that one entity includes or embeds the script of another entity within it.
-
D.
hasPreCodeStatus
Indicates that an entity held a specific code-related status or classification at some earlier point in time.
-
E.
hasScriptRegulator
Indicates that an entity has an associated mechanism or component that controls or governs its script or scripting behavior.
- 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6200ac60481909895c61d050b1338 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 21, 2026, 2:03 p.m.