Triple
T14684064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nasir Jung |
E344863
|
entity |
| Predicate | opponent |
P437
|
FINISHED |
| Object | Chanda Sahib |
E68823
|
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: Chanda Sahib | Statement: [Nasir Jung, opponent, Chanda Sahib]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chanda Sahib Context triple: [Nasir Jung, opponent, Chanda Sahib]
-
A.
Chanda Sahib
chosen
Chanda Sahib was an 18th-century Indian ruler and military leader who played a central role in the Carnatic Wars, notably opposing the British during conflicts such as the Siege of Arcot.
-
B.
Raza Sahib
Raza Sahib was an 18th-century military leader in southern India who commanded forces during the Siege of Arcot in the Carnatic Wars.
-
C.
Jam Sahib
Jam Sahib is the hereditary royal title borne by the rulers of the former princely state of Nawanagar in present-day Gujarat, India.
-
D.
Takht Singh
Takht Singh was a 19th-century Maharaja of Jodhpur known for consolidating Marwar under British paramountcy and maintaining the prominence of the Rathore dynasty.
-
E.
Sahiban
Sahiban is a tragic heroine from the Punjabi romantic epic "Mirza Sahiban," renowned in South Asian folklore for her ill-fated love story with Mirza.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56bdb8081909ff86440ba20fb1f |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf080b7508190ac99b8bb6cfb1881 |
completed | May 8, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:28 a.m.