Triple
T34805612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shyama Kund |
E1003344
|
entity |
| Predicate | languageName-en |
P50222
|
FINISHED |
| Object | Shyama Kund |
—
|
NE NERFINISHED |
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: Shyama Kund | Statement: [Shyama Kund, languageName-en, Shyama Kund]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageName-en Context triple: [Shyama Kund, languageName-en, Shyama Kund]
-
A.
languageName
Indicates the specific name assigned to a language in the relationship.
-
B.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
C.
languageLabel
chosen
Indicates the human-readable name or label of a language associated with an entity or resource.
-
D.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a008ebb22408190a2293bced40a7e53 |
completed | May 10, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_6a008e8715dc8190ab23292605901bf4 |
completed | May 10, 2026, 1:56 p.m. |
Created at: May 3, 2026, 3:59 p.m.