Triple

T38663963
Position Surface form Disambiguated ID Type / Status
Subject Mughal Subah of Lahore E940404 entity
Predicate borderedBy P224 FINISHED
Object Subah of Multan
The Subah of Multan was an important Mughal imperial province in northwestern South Asia, centered on the historic city of Multan and serving as a strategic frontier region.
E2279583 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: Subah of Multan | Statement: [Mughal Subah of Lahore, borderedBy, Subah of Multan]
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: Subah of Multan
Triple: [Mughal Subah of Lahore, borderedBy, Subah of Multan]
Generated description
The Subah of Multan was an important Mughal imperial province in northwestern South Asia, centered on the historic city of Multan and serving as a strategic frontier 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_69f76edfde348190bf6529d9f49ecd62 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdbf07fd48190a97ee5e1ee1356e0 completed May 7, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd6785c08190b2f7c93735c31c3c completed June 29, 2026, 5:06 a.m.
NEDg Description generation batch_6a41fea52f9c81908d9f297937f93120 completed June 29, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_6a41ff511ed481909140acbd554ecce3 completed June 29, 2026, 5:14 a.m.
Created at: May 3, 2026, 4:33 p.m.