Triple
T11122022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaya Bharata Jananiya Tanujate |
E263039
|
entity |
| Predicate | titleInKannadaScript |
P97664
|
FINISHED |
| Object | ಜಯ ಭಾರತ ಜನನಿಯ ತನುಜಾತೆ |
—
|
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: ಜಯ ಭಾರತ ಜನನಿಯ ತನುಜಾತೆ | Statement: [Jaya Bharata Jananiya Tanujate, titleInKannadaScript, ಜಯ ಭಾರತ ಜನನಿಯ ತನುಜಾತೆ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleInKannadaScript Context triple: [Jaya Bharata Jananiya Tanujate, titleInKannadaScript, ಜಯ ಭಾರತ ಜನನಿಯ ತನುಜಾತೆ]
-
A.
titleInTamilScript
Indicates that the title of an entity is expressed or recorded in the Tamil script.
-
B.
titleInBengaliScript
Indicates that the title of an entity is written or represented in the Bengali script.
-
C.
titleInLatinScript
Indicates that the title of an entity is written or represented using a Latin-based writing system.
-
D.
titleInKorean
Indicates that an entity has a specific title expressed in the Korean language.
-
E.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79afa0ab88190ab6d61df8cf485ec |
completed | April 9, 2026, 12:26 p.m. |
| PD | Predicate disambiguation | batch_69d7441efe948190ae4ab020121e169d |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d75112eb1c8190ba1dd51e42e8a7e8 |
completed | April 9, 2026, 7:11 a.m. |
Created at: April 8, 2026, 9:28 p.m.