Triple
T16608000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanheya Misl |
E403493
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Majha |
E63912
|
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: Majha | Statement: [Kanheya Misl, historicalRegion, Majha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Majha Context triple: [Kanheya Misl, historicalRegion, Majha]
-
A.
Majha
chosen
Majha is a culturally significant region of Punjab in northern India, traditionally known as the heartland of Sikh culture and history.
-
B.
Mam Maya
Mam Maya are an Indigenous Maya people of the highlands of Guatemala and parts of Mexico, known for their distinct Mayan language, traditional weaving, and resilient cultural practices.
-
C.
Majhli Didi
Majhli Didi is a 1967 Hindi drama film, based on a story by Sarat Chandra Chattopadhyay and noted for its sensitive portrayal of rural life and relationships.
-
D.
Mahjoor
Mahjoor was a renowned Kashmiri poet celebrated for revitalizing modern Kashmiri literature and expressing the social and cultural aspirations of the Kashmiri people.
-
E.
Marga Marga
Marga Marga is a river in central Chile whose name was adopted by the surrounding Province of Marga Marga.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36093901881909b85af47f75879a9 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075aa79408190b395d4cd9c6c1cb7 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:17 a.m.