Triple
T1031847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navjivan |
E22269
|
entity |
| Predicate | languageOfPublication |
P876
|
FINISHED |
| Object | Gujarati |
E8599
|
NE 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: Gujarati | Statement: [Navjivan, languageOfPublication, Gujarati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gujarati Context triple: [Navjivan, languageOfPublication, Gujarati]
-
A.
Gujarati
chosen
Gujarati is an Indo-Aryan language primarily spoken in the Indian state of Gujarat and by Gujarati communities worldwide.
-
B.
Hindi
Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
-
C.
Sindhi
Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
-
D.
Sant Bhasha
Sant Bhasha is a historical North Indian devotional literary language used in Sikh and related spiritual poetry, written in the Gurmukhi script.
-
E.
Gujarati script
The Gujarati script is an abugida used primarily to write the Gujarati language and related Indo-Aryan languages, derived from the Devanagari script and characterized by the absence of the horizontal headline.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b811916481908c05c2dd5ec802ec |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c15bb8481909ba68f5807581b18 |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:41 p.m.