Triple

T34362431
Position Surface form Disambiguated ID Type / Status
Subject Kamareddy district E881912 entity
Predicate hasLocalGovernment P2820 FINISHED
Object Zilla Parishad Kamareddy
Zilla Parishad Kamareddy is the apex rural local government body responsible for planning and overseeing development programs and services across Kamareddy district in Telangana, India.
E2093868 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: Zilla Parishad Kamareddy | Statement: [Kamareddy district, hasLocalGovernment, Zilla Parishad Kamareddy]
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: Zilla Parishad Kamareddy
Triple: [Kamareddy district, hasLocalGovernment, Zilla Parishad Kamareddy]
Generated description
Zilla Parishad Kamareddy is the apex rural local government body responsible for planning and overseeing development programs and services across Kamareddy district in Telangana, India.

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_69f349be5c9c81908dc726ae1f4c68f2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7182aacb481908edc5ceead43bb01 completed May 3, 2026, 9:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3704a7d1208190b2402ac7c4f30efc completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a370607445c8190a79d3d75eff14461 completed June 20, 2026, 9:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3706fc215c8190b785c1abb5b08193 completed June 20, 2026, 9:32 p.m.
Created at: May 1, 2026, 1:58 a.m.