Triple

T27280497
Position Surface form Disambiguated ID Type / Status
Subject Mihirakula E688317 entity
Predicate opponent P437 FINISHED
Object Baladitya of Magadha
Baladitya of Magadha was an Indian ruler of the Gupta period, remembered in tradition for resisting the Huna king Mihirakula and symbolizing the late Gupta struggle against foreign invasions.
 E1765173 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: Baladitya of Magadha | Statement: [Mihirakula, opponent, Baladitya of Magadha]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Baladitya of Magadha
Triple: [Mihirakula, opponent, Baladitya of Magadha]
Generated description
Baladitya of Magadha was an Indian ruler of the Gupta period, remembered in tradition for resisting the Huna king Mihirakula and symbolizing the late Gupta struggle against foreign invasions.

Provenance (5 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_69ef355998e08190bdff849e8f33adce completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6272d55e48190bb2eb6bd4c120daf completed May 2, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a126293a2008190a716ef1f1d5841f8 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1268eb06cc8190a9bcb4397775c34c completed May 24, 2026, 2:56 a.m.
NED2 Entity disambiguation (via description) batch_6a126983a194819093db115c63acc22f completed May 24, 2026, 2:59 a.m.
Created at: April 27, 2026, 11:06 a.m.