Triple
T4951238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krishna Hutheesing |
E111172
|
entity |
| Predicate | writing language |
P38007
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Krishna Hutheesing, writing language, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writing language Context triple: [Krishna Hutheesing, writing language, English]
-
A.
writesLanguage
chosen
Indicates that an entity produces written content in a particular language.
-
B.
written
Indicates that one entity has created or authored a text, document, or written work involving or about another entity.
-
C.
writingForm
Indicates the specific script, notation, or written representation used to express a piece of language or content.
-
D.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
E.
writingComponent
Indicates that one entity is a written part or element that contributes to the composition or structure of another entity.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b561ec81908083225269222e96 |
completed | March 20, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.