Triple

T2423745
Position Surface form Disambiguated ID Type / Status
Subject Haripur E53477 entity
Predicate nearbyCity P350 FINISHED
Object Islamabad E5692 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: Islamabad | Statement: [Haripur, nearbyCity, Islamabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Islamabad
Context triple: [Haripur, nearbyCity, Islamabad]
  • A. Islamabad chosen
    Islamabad is Pakistan’s planned, modern capital city known for its high standard of living, greenery, and role as the country’s political and administrative center.
  • 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. Lahore
    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.
  • D. 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.
  • E. 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.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc973aee08190b543492f436f3fe5 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69b402a702a081909319ba32990fa010 completed March 13, 2026, 12:27 p.m.
Created at: March 6, 2026, 9:42 p.m.