Triple
T15057350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patna division |
E379529
|
entity |
| Predicate | languageUsed |
P238
|
FINISHED |
| Object | Magahi |
E53011
|
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: Magahi | Statement: [Patna division, languageUsed, Magahi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magahi Context triple: [Patna division, languageUsed, Magahi]
-
A.
Magahi
chosen
Magahi is an Eastern Indo-Aryan language spoken primarily in the Indian state of Bihar and surrounding regions.
-
B.
Mohanchoti
Mohanchoti is an island located within Lake Pichola in Udaipur, Rajasthan, India.
-
C.
Majangir
Majangir is an ethnic group of southwestern Ethiopia known for speaking the Majang language, part of the Surmic branch of the Nilo-Saharan language family.
-
D.
Gamgadhi
Gamgadhi is a remote town in northwestern Nepal that serves as an access point and administrative hub for the area around Rara National Park.
-
E.
Maihar
Maihar is a town in Madhya Pradesh, India, renowned for its revered Maa Sharda Devi temple and its rich Hindustani classical music heritage.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda937f788190899d81bbb2084443 |
completed | April 15, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5c11fb4819086c4b85a8d29ccf7 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 3:01 a.m.