Triple

T28026925
Position Surface form Disambiguated ID Type / Status
Subject Moti Bazaar, Rawalpindi E708148 entity
Predicate nearbyPlace P2064 FINISHED
Object Old Rawalpindi city area
Old Rawalpindi city area is the historic core of Rawalpindi, Pakistan, characterized by its narrow streets, traditional bazaars, and preserved colonial and pre-colonial architecture.
 E1799549 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: Old Rawalpindi city area | Statement: [Moti Bazaar, Rawalpindi, nearbyPlace, Old Rawalpindi city area]
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: Old Rawalpindi city area
Triple: [Moti Bazaar, Rawalpindi, nearbyPlace, Old Rawalpindi city area]
Generated description
Old Rawalpindi city area is the historic core of Rawalpindi, Pakistan, characterized by its narrow streets, traditional bazaars, and preserved colonial and pre-colonial architecture.

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_69ef9b6bdd9c8190bb3a574a03774ad1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63c6ef4348190821f991c682a6894 completed May 2, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8ab2a148190a2822ac1e056f96d completed May 26, 2026, 3:13 p.m.
NEDg Description generation batch_6a15ba3cee908190ae81c8f0d3b0b919 completed May 26, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_6a15bb3f1c3c8190ad54f1af031c89cb completed May 26, 2026, 3:24 p.m.
Created at: April 27, 2026, 8:13 p.m.