Triple

T35404068
Position Surface form Disambiguated ID Type / Status
Subject Faizabad district E1023316 entity
Predicate governedBy P46 FINISHED
Object Faizabad district administration
Faizabad district administration is the local governmental authority responsible for managing public services, law and order, and development activities within Faizabad district.
E1023316 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: Faizabad district administration | Statement: [Faizabad district, governedBy, Faizabad district administration]
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: Faizabad district administration
Triple: [Faizabad district, governedBy, Faizabad district administration]
Generated description
Faizabad district administration is the local governmental authority responsible for managing public services, law and order, and development activities within Faizabad district.

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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7953fa72c8190bd737ef5dfa0ffc0 completed May 3, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382cce7ad481908d2c71cd31a0f6c9 completed June 21, 2026, 6:26 p.m.
NEDg Description generation batch_6a382dbfa90081908a3785cd1d44fc23 completed June 21, 2026, 6:30 p.m.
NED2 Entity disambiguation (via description) batch_6a382e5f437481909c6c9f085168bfec completed June 21, 2026, 6:33 p.m.
Created at: May 3, 2026, 4:03 p.m.