Triple

T5709417
Position Surface form Disambiguated ID Type / Status
Subject Hazarajat E125866 entity
Predicate majorCity P316 FINISHED
Object Daykundi
Daykundi is a central Afghan province within the Hazarajat region, known for its predominantly Hazara population and mountainous terrain.
 E542625 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: Daykundi | Statement: [Hazarajat, majorCity, Daykundi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daykundi
Context triple: [Hazarajat, majorCity, Daykundi]
  • A. Qazigund
    Qazigund is a town in the Kashmir Valley of northern India, known as a key transit point and gateway between the Jammu region and the Kashmir Valley.
  • B. Asadabad
    Asadabad is a small but strategically important city in eastern Afghanistan, serving as the capital of Kunar Province near the Pakistani border.
  • C. Mardan
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • D. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • E. Golestan
    Golestan is a classic 13th-century Persian literary work by Saadi that blends prose and poetry to convey moral lessons and social commentary.
  • 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: Daykundi
Triple: [Hazarajat, majorCity, Daykundi]
Generated description
Daykundi is a central Afghan province within the Hazarajat region, known for its predominantly Hazara population and mountainous terrain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daykundi
Target entity description: Daykundi is a central Afghan province within the Hazarajat region, known for its predominantly Hazara population and mountainous terrain.
  • A. Qazigund
    Qazigund is a town in the Kashmir Valley of northern India, known as a key transit point and gateway between the Jammu region and the Kashmir Valley.
  • B. Asadabad
    Asadabad is a small but strategically important city in eastern Afghanistan, serving as the capital of Kunar Province near the Pakistani border.
  • C. Mardan
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • D. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • E. Golestan
    Golestan is a classic 13th-century Persian literary work by Saadi that blends prose and poetry to convey moral lessons and social commentary.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0248c3dac8190824fca9ddde89665 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a6f5ac08190b5acbccea756d2de completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c062029e3c8190ade3f0836d6b3842 completed March 22, 2026, 9:41 p.m.
NED2 Entity disambiguation (via description) batch_69c06268eb0c8190959ba762c2d9b47d completed March 22, 2026, 9:43 p.m.
Created at: March 22, 2026, 3:46 p.m.