Triple

T16185029
Position Surface form Disambiguated ID Type / Status
Subject Chief Minister of Gilgit-Baltistan E392778 entity
Predicate officeHolder P537 FINISHED
Object Gulbar Khan
Gulbar Khan is a Pakistani politician serving as the Chief Minister of the Gilgit-Baltistan region.
E1199961 NE FINISHED

How this triple was built (4 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: Gulbar Khan | Statement: [Chief Minister of Gilgit-Baltistan, officeHolder, Gulbar Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gulbar Khan
Context triple: [Chief Minister of Gilgit-Baltistan, officeHolder, Gulbar Khan]
  • A. Diler Khan
    Diler Khan was a prominent Mughal military general known for leading imperial campaigns in the Deccan, particularly against the Sultanate of Bijapur.
  • B. Barak Khan
    Barak Khan was a 13th-century Mongol ruler who led the Blue Horde, a division of the Golden Horde in Central Asia.
  • C. Bori Khan
    Bori Khan is the primary Rouran warrior antagonist in Disney’s 2020 live-action film "Mulan," leading an invasion of China against the imperial army.
  • D. Sher Afghan Khan
    Sher Afghan Khan was a Mughal nobleman and jagirdar in Bengal, best known as the first husband of Nur Jahan, the future empress of the Mughal Empire.
  • E. Hasan Bughra Khan
    Hasan Bughra Khan was a prominent ruler of the Kara-Khanid dynasty, known for consolidating its power in Central Asia during the late 10th century.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gulbar Khan
Triple: [Chief Minister of Gilgit-Baltistan, officeHolder, Gulbar Khan]
Generated description
Gulbar Khan is a Pakistani politician serving as the Chief Minister of the Gilgit-Baltistan region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gulbar Khan
Target entity description: Gulbar Khan is a Pakistani politician serving as the Chief Minister of the Gilgit-Baltistan region.
  • A. Diler Khan
    Diler Khan was a prominent Mughal military general known for leading imperial campaigns in the Deccan, particularly against the Sultanate of Bijapur.
  • B. Barak Khan
    Barak Khan was a 13th-century Mongol ruler who led the Blue Horde, a division of the Golden Horde in Central Asia.
  • C. Bori Khan
    Bori Khan is the primary Rouran warrior antagonist in Disney’s 2020 live-action film "Mulan," leading an invasion of China against the imperial army.
  • D. Sher Afghan Khan
    Sher Afghan Khan was a Mughal nobleman and jagirdar in Bengal, best known as the first husband of Nur Jahan, the future empress of the Mughal Empire.
  • E. Hasan Bughra Khan
    Hasan Bughra Khan was a prominent ruler of the Kara-Khanid dynasty, known for consolidating its power in Central Asia during the late 10th century.
  • F. None of above. chosen

Provenance (5 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22060dcf88190b7c662946a5f0191 completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffff0550b48190ac84946b7254552b completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a0000a8a74c8190925c4140cf4a8520 completed May 10, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_6a0004ceda8c8190a358f58f76116a7f completed May 10, 2026, 4:08 a.m.
Created at: April 10, 2026, 5:02 a.m.