Triple
T11924672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maharana Pratap |
E283748
|
entity |
| Predicate | opponent |
P437
|
FINISHED |
| Object | Akbar |
E14445
|
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: Akbar | Statement: [Maharana Pratap, opponent, Akbar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akbar Context triple: [Maharana Pratap, opponent, Akbar]
-
A.
Akbar
chosen
Akbar was a powerful 16th-century Mughal emperor renowned for expanding and consolidating his empire in India and promoting religious tolerance and administrative reforms.
-
B.
Akbar Khan
Akbar Khan was an Afghan military leader and prince known for leading resistance against British forces during the First Anglo-Afghan War in the 19th century.
-
C.
Sultan Muhammad Akbar
Sultan Muhammad Akbar was a Mughal prince of the 17th century, known as the son of Emperor Aurangzeb and his chief consort Dilras Banu Begum.
-
D.
Akbar Muhammad
Akbar Muhammad was an American scholar and activist known for his work on African and Islamic studies and as a prominent member of the Nation of Islam.
-
E.
Shah Jahan
Shah Jahan was a 17th-century Mughal emperor best known for commissioning the Taj Mahal and overseeing a golden age of Indo-Islamic art and architecture in India.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8e2fc648190a446c1917db1c7d9 |
completed | April 10, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f44042cf1c81909de44acfe1202482 |
completed | May 1, 2026, 5:55 a.m. |
Created at: April 8, 2026, 9:45 p.m.