Triple
T5888508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tansen Music Festival |
E130928
|
entity |
| Predicate | honours |
P107
|
FINISHED |
| Object | Mian Tansen |
E552263
|
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: Mian Tansen | Statement: [Tansen Music Festival, honours, Mian Tansen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mian Tansen Context triple: [Tansen Music Festival, honours, Mian Tansen]
-
A.
Mian Tansen
chosen
Mian Tansen was a legendary 16th-century Hindustani classical musician and one of the most celebrated court singers of Mughal emperor Akbar.
-
B.
Tansen
Tansen is a historic hill town in western Nepal known for its Newari architecture, panoramic Himalayan views, and cultural significance.
-
C.
Meera Bai
Meera Bai was a 16th-century Hindu mystic poet-saint of the Bhakti movement, renowned for her devotional songs dedicated to Lord Krishna.
-
D.
Laxmibai
Laxmibai was the wife of the renowned Kannada poet and Jnanpith awardee D. R. Bendre.
-
E.
Janabai
Janabai was a 13th-century Marathi saint-poet and devotee of Vithoba, renowned for her abhangas and her prominent role in the Bhakti movement.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036af6330819081d9fa98a8c26633 |
completed | March 22, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0bff9ecdc819098823b003cec66a2 |
completed | March 23, 2026, 4:22 a.m. |
Created at: March 22, 2026, 3:58 p.m.