Triple

T3208491
Position Surface form Disambiguated ID Type / Status
Subject Civil Services Academy Lahore E67220 entity
Predicate city P40 FINISHED
Object Lahore E67437 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: Lahore | Statement: [Civil Services Academy Lahore, city, Lahore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lahore
Context triple: [Civil Services Academy Lahore, city, Lahore]
  • A. Lahore chosen
    Lahore is a major cultural, historical, and economic center of Pakistan, known for its rich Mughal heritage, educational institutions, and role in the region’s political history.
  • B. Rawalpindi
    Rawalpindi is a major city in Pakistan’s Punjab province, historically significant as a former temporary national capital and now a key commercial and military center.
  • C. Karachi
    Karachi is Pakistan’s sprawling economic hub and major port city on the Arabian Sea, known for its diverse population and central role in the country’s finance, industry, and culture.
  • D. Peshawar
    Peshawar is one of Pakistan’s oldest and largest cities, a historic cultural and economic hub located near the Khyber Pass in the country’s northwest.
  • E. Multan
    Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaa59888481908bdaefa1968d7f04 completed March 8, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd567a48b881908e4bfec70943eb60 completed March 20, 2026, 2:15 p.m.
Created at: March 8, 2026, 3:07 p.m.