Triple

T23194175
Position Surface form Disambiguated ID Type / Status
Subject Gah E579828 entity
Predicate hasNearbyCity 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: [Gah, hasNearbyCity, Islamabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Islamabad
Context triple: [Gah, hasNearbyCity, 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_69e24600eed08190bd7e5295653a1503 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18fda64cc8190aeb5ccd8d8d20858 completed April 29, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c3f49f3208190bbbc705e2f8b08ee completed May 19, 2026, 10:45 a.m.
Created at: April 17, 2026, 4:06 p.m.