Triple
T11688879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S. V. Krishnamoorthy Rao |
E277815
|
entity |
| Predicate | nativeLanguageContext |
P101265
|
FINISHED |
| Object | Indian political sphere |
—
|
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: Indian political sphere | Statement: [S. V. Krishnamoorthy Rao, nativeLanguageContext, Indian political sphere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeLanguageContext Context triple: [S. V. Krishnamoorthy Rao, nativeLanguageContext, Indian political sphere]
-
A.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
B.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
C.
languageFamilyContext
Indicates the broader linguistic family or grouping within which a particular language or linguistic element is situated.
-
D.
localLanguageName
Indicates the name of a language as it is written or referred to in its own local or native form.
-
E.
primaryLocalLanguageFamily
Indicates the main linguistic family to which the predominant local language of an entity belongs.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a478f4c481908b2ba7b70972590d |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d89546a8688190b51455b5e12caf91 |
completed | April 10, 2026, 6:14 a.m. |
Created at: April 8, 2026, 9:40 p.m.