Triple

T30936563
Position Surface form Disambiguated ID Type / Status
Subject Dhenkanal district E788138 entity
Predicate borderedBy P224 FINISHED
Object Khurda district
Khurda district is an administrative district in the Indian state of Odisha, known for containing the state capital Bhubaneswar and serving as a major political and economic hub of the region.
E1947469 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: Khurda district | Statement: [Dhenkanal district, borderedBy, Khurda district]
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: Khurda district
Triple: [Dhenkanal district, borderedBy, Khurda district]
Generated description
Khurda district is an administrative district in the Indian state of Odisha, known for containing the state capital Bhubaneswar and serving as a major political and economic hub of the region.

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_69f224c0b7fc819090cb89df60d23653 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692e5069c81908013503ba8d065d7 completed May 3, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a293895fd348190ac766f445d81f966 completed June 10, 2026, 10:12 a.m.
NEDg Description generation batch_6a293c7e72f4819090260ad1d80770b7 completed June 10, 2026, 10:29 a.m.
NED2 Entity disambiguation (via description) batch_6a293d3b720c8190afd50e5e7c2a0997 completed June 10, 2026, 10:32 a.m.
Created at: April 29, 2026, 8:52 p.m.