Triple

T13210049
Position Surface form Disambiguated ID Type / Status
Subject Umarkot Fort E314465 entity
Predicate locatedIn P40 FINISHED
Object Umarkot E79535 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: Umarkot | Statement: [Umarkot Fort, locatedIn, Umarkot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umarkot
Context triple: [Umarkot Fort, locatedIn, Umarkot]
  • A. Umarkot chosen
    Umarkot is a historic town in the Sindh province of Pakistan, traditionally known as the birthplace of the Mughal emperor Akbar.
  • B. Karimabad
    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.
  • C. Karimabad
    Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
  • D. Skardu
    Skardu is a major town in northern Pakistan’s Gilgit-Baltistan region, known as a gateway to the Karakoram mountains and popular for its high-altitude trekking and scenic landscapes.
  • E. Pul-e Khumri
    Pul-e Khumri is a key industrial and administrative city in northern Afghanistan, serving as the capital of Baghlan Province and an important regional transport hub.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9e072c8190b66e2c2430628ed0 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d7edb40819095dfa45d3c61a0e3 completed May 3, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:17 p.m.