Triple
T8339439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Baksar |
E195872
|
entity |
| Predicate | opponent |
P437
|
FINISHED |
| Object | Mir Qasim |
E175462
|
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: Mir Qasim | Statement: [Battle of Baksar, opponent, Mir Qasim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mir Qasim Context triple: [Battle of Baksar, opponent, Mir Qasim]
-
A.
Mir Qasim
chosen
Mir Qasim was the Nawab of Bengal in the mid-18th century, known for his resistance to British expansion in India and his defeat in the Battle of Buxar in 1764.
-
B.
Quddus
Quddus is a television personality best known as one of the prominent hosts of MTV’s music video countdown show "Total Request Live" in the early 2000s.
-
C.
Thadiq
Thadiq is a town in central Saudi Arabia known for its traditional architecture and location within the Riyadh administrative region.
-
D.
Khudayar Khan
Khudayar Khan was a 19th-century ruler of the Kokand Khanate in Central Asia, known for his turbulent reign marked by internal strife and increasing Russian influence in the region.
-
E.
Alamuddin
Alamuddin is the Lebanese Druze family name of prominent human rights lawyer Amal Clooney (née Amal Alamuddin).
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd7a3888190b54306ed862aded4 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde79e916c8190afc90c3b12c68caf |
completed | April 2, 2026, 3:50 a.m. |
Created at: March 30, 2026, 5:57 p.m.