Triple

T14818407
Position Surface form Disambiguated ID Type / Status
Subject South Khorasan Province E348379 entity
Predicate hasCity P316 FINISHED
Object Qaen
Qaen is a historic city in eastern Iran known as a regional center for saffron production and traditional crafts.
E1156976 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: Qaen | Statement: [South Khorasan Province, hasCity, Qaen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qaen
Context triple: [South Khorasan Province, hasCity, Qaen]
  • 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. Piranshahr
    Piranshahr is a predominantly Kurdish city in northwestern Iran known for its mountainous surroundings and role as a regional commercial center.
  • C. Taleqan
    Taleqan is a small mountainous city in northern Iran known for its cool climate, natural landscapes, and traditional rural architecture.
  • D. Qaem Shahr
    Qaem Shahr is a major industrial and commercial city in northern Iran, located in the lush, Caspian coastal region of Mazandaran.
  • E. Khodjend
    Khodjend is the former name of Khujand, one of the oldest cities in Central Asia and a major cultural and economic center in northern Tajikistan.
  • 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: Qaen
Triple: [South Khorasan Province, hasCity, Qaen]
Generated description
Qaen is a historic city in eastern Iran known as a regional center for saffron production and traditional crafts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Qaen
Target entity description: Qaen is a historic city in eastern Iran known as a regional center for saffron production and traditional crafts.
  • 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. Piranshahr
    Piranshahr is a predominantly Kurdish city in northwestern Iran known for its mountainous surroundings and role as a regional commercial center.
  • C. Taleqan
    Taleqan is a small mountainous city in northern Iran known for its cool climate, natural landscapes, and traditional rural architecture.
  • D. Qaem Shahr
    Qaem Shahr is a major industrial and commercial city in northern Iran, located in the lush, Caspian coastal region of Mazandaran.
  • E. Khodjend
    Khodjend is the former name of Khujand, one of the oldest cities in Central Asia and a major cultural and economic center in northern Tajikistan.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff218f11008190bd4837f900746d1a completed May 9, 2026, 11:59 a.m.
NEDg Description generation batch_69ff2248c514819084cfe899478129d9 completed May 9, 2026, 12:02 p.m.
NED2 Entity disambiguation (via description) batch_69ff229cec3081908c7f904a09613d01 completed May 9, 2026, 12:03 p.m.
Created at: April 10, 2026, 1:50 a.m.