Triple

T35053007
Position Surface form Disambiguated ID Type / Status
Subject MCB Tower E1011383 entity
Predicate owner P347 FINISHED
Object MCB Bank Limited
MCB Bank Limited is one of Pakistan’s leading commercial banks, offering a wide range of retail and corporate banking services across an extensive domestic and international branch network.
E2126966 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: MCB Bank Limited | Statement: [MCB Tower, owner, MCB Bank Limited]
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: MCB Bank Limited
Triple: [MCB Tower, owner, MCB Bank Limited]
Generated description
MCB Bank Limited is one of Pakistan’s leading commercial banks, offering a wide range of retail and corporate banking services across an extensive domestic and international branch network.

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_69f76dcfdda48190b1ebae5da8b54f12 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f785cef994819084b0a5574efc0674 completed May 3, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37d942367c8190a626850f6ac58d63 completed June 21, 2026, 12:29 p.m.
NEDg Description generation batch_6a37da92f6b48190a937a9c04bd5d064 completed June 21, 2026, 12:35 p.m.
NED2 Entity disambiguation (via description) batch_6a37dbed7540819081bd95af5520b163 completed June 21, 2026, 12:41 p.m.
Created at: May 3, 2026, 4:01 p.m.