Triple

T29634572
Position Surface form Disambiguated ID Type / Status
Subject Nandivarman II E755676 entity
Predicate successor P78 FINISHED
Object Dantivarman
Dantivarman was a Pallava king of South India who ruled in the late 8th and early 9th centuries CE, overseeing a period of political decline and regional challenges for the dynasty.
E1881158 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: Dantivarman | Statement: [Nandivarman II, successor, Dantivarman]
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: Dantivarman
Triple: [Nandivarman II, successor, Dantivarman]
Generated description
Dantivarman was a Pallava king of South India who ruled in the late 8th and early 9th centuries CE, overseeing a period of political decline and regional challenges for the dynasty.

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_69f0ef88fbe081908f0ad90c1c413f1c completed April 28, 2026, 5:34 p.m.
NER Named-entity recognition batch_69f66e68f5588190b41a2060d3aea12f completed May 2, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa63d4788190bd71f8579e09e62e completed June 8, 2026, 11:41 a.m.
NEDg Description generation batch_6a26b01a27148190aa0135f779819255 completed June 8, 2026, 12:05 p.m.
NED2 Entity disambiguation (via description) batch_6a26b4f2ca348190b487f39e75b45b4f completed June 8, 2026, 12:26 p.m.
Created at: April 28, 2026, 6:43 p.m.