Triple

T38019365
Position Surface form Disambiguated ID Type / Status
Subject Bodh Gaya block E948584 entity
Predicate partOf P40 FINISHED
Object state of Bihar, India
The state of Bihar in India is a populous eastern state known for its rich ancient history, including sites like Nalanda and Bodh Gaya, and its predominantly agrarian economy.
E2258706 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: state of Bihar, India | Statement: [Bodh Gaya block, partOf, state of Bihar, India]
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: state of Bihar, India
Triple: [Bodh Gaya block, partOf, state of Bihar, India]
Generated description
The state of Bihar in India is a populous eastern state known for its rich ancient history, including sites like Nalanda and Bodh Gaya, and its predominantly agrarian economy.

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_69f76efc10448190aff5fb566b98f952 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc96f90b08190bebd5912bab7de3f completed May 6, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41711136d88190a9b7eb4ad23dd688 completed June 28, 2026, 7:08 p.m.
NEDg Description generation batch_6a41752b417481908d56f86c496380b2 completed June 28, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a417577345c8190a6df22c44e567d58 completed June 28, 2026, 7:26 p.m.
Created at: May 3, 2026, 4:20 p.m.