Triple

T13633536
Position Surface form Disambiguated ID Type / Status
Subject Rakaposhi E325785 entity
Predicate near P350 FINISHED
Object Karimabad E271539 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: Karimabad | Statement: [Rakaposhi, near, Karimabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karimabad
Context triple: [Rakaposhi, near, Karimabad]
  • A. Karimabad chosen
    Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
  • B. Karimabad
    Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
  • C. Umarkot
    Umarkot is a historic town in the Sindh province of Pakistan, traditionally known as the birthplace of the Mughal emperor Akbar.
  • D. Khoshbagh
    Khoshbagh is a historic garden-cemetery complex in Murshidabad, West Bengal, known as the burial place of several Nawabs of Bengal.
  • E. Jauharabad
    Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a490508190924ac40f1dd519d6 completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b05f0e948190b7f22d071ad54283 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9:51 p.m.