Triple

T34869751
Position Surface form Disambiguated ID Type / Status
Subject Nayabad E1005713 entity
Predicate isGovernedAsPartOf P33581 FINISHED
Object Karachi City District Government
Karachi City District Government was the former local government body responsible for administering and managing municipal services and development across the metropolitan area of Karachi, Pakistan.
E2127770 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: Karachi City District Government | Statement: [Nayabad, isGovernedAsPartOf, Karachi City District Government]
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: Karachi City District Government
Triple: [Nayabad, isGovernedAsPartOf, Karachi City District Government]
Generated description
Karachi City District Government was the former local government body responsible for administering and managing municipal services and development across the metropolitan area of Karachi, Pakistan.

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_69f76dbde1c08190a24e7f9beb564c8d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7818336108190beeedd2123e28afd completed May 3, 2026, 5:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d93847108190bc44b92e7a7f9171 completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37db62c9f4819092095177cc349683 completed June 21, 2026, 12:38 p.m.
NED2 Entity disambiguation (via description) batch_6a37dcf7cdb08190a6a043d8a3e5d5f8 completed June 21, 2026, 12:45 p.m.
Created at: May 3, 2026, 4 p.m.